29 results on '"Legowski, Elizabeth A."'
Search Results
2. Emotional Distress Predicts Reduced Type 2 Diabetes Treatment Adherence in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE).
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Hoogendoorn, Claire J., Krause-Steinrauf, Heidi, Uschner, Diane, Wen, Hui, Presley, Caroline A., Legowski, Elizabeth A., Naik, Aanand D., Golden, Sherita Hill, Arends, Valerie L., Brown-Friday, Janet, Krakoff, Jonathan A., Suratt, Colleen E., Waltje, Andrea H., Cherrington, Andrea L., Gonzalez, Jeffrey S., Crandall, J.P., McKee, M.D., Behringer-Massera, S., Brown-Friday, J., and Xhori, E.
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TYPE 2 diabetes ,PSYCHOLOGICAL distress ,PATIENT compliance ,COMPARATIVE method ,ETHNIC differences ,PATIENT satisfaction - Abstract
OBJECTIVE: We examined longitudinal associations between emotional distress (specifically, depressive symptoms and diabetes distress) and medication adherence in Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE), a large randomized controlled trial comparing four glucose-lowering medications added to metformin in adults with relatively recent-onset type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: The Emotional Distress Substudy assessed medication adherence, depressive symptoms, and diabetes distress in 1,739 GRADE participants via self-completed questionnaires administered biannually up to 3 years. We examined baseline depressive symptoms and diabetes distress as predictors of medication adherence over 36 months. Bidirectional visit-to-visit relationships were also examined. Treatment satisfaction, beliefs about medication, diabetes care self-efficacy, and perceived control over diabetes were evaluated as mediators of longitudinal associations. RESULTS: At baseline, mean ± SD age of participants (56% of whom were White, 17% Hispanic/Latino, 18% Black, and 66% male) was 58.0 ± 10.2 years, diabetes duration 4.2 ± 2.8 years, HbA
1c 7.5% ± 0.5%, and medication adherence 89.9% ± 11.1%. Higher baseline depressive symptoms and diabetes distress were independently associated with lower adherence over 36 months (P < 0.001). Higher depressive symptoms and diabetes distress at one visit predicted lower adherence at the subsequent 6-month visit (P < 0.0001) but not vice versa. Treatment assignment did not moderate relationships. Patient-reported concerns about diabetes medications mediated the largest percentage (11.9%–15.5%) of the longitudinal link between emotional distress and adherence. CONCLUSIONS: Depressive symptoms and diabetes distress both predict lower adherence to glucose-lowering medications over time among adults with T2DM. Addressing emotional distress and concerns about anticipated negative effects of taking these treatments may be important to support diabetes treatment adherence. [ABSTRACT FROM AUTHOR]- Published
- 2024
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3. The Use of Rescue Insulin in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE).
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Hollander, Priscilla A., Krause-Steinrauf, Heidi, Butera, Nicole M., Kazemi, Erin J., Ahmann, Andrew J., Fattaleh, Basma N., Johnson, Mary L., Killean, Tina, Lagari, Violet S., Larkin, Mary E., Legowski, Elizabeth A., Rasouli, Neda, Willis, Holly J., Martin, Catherine L., Crandall, J.P., McKee, M.D., Behringer-Massera, S., Brown-Friday, J., Xhori, E., and Ballentine-Cargill, K.
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COMPARATIVE method ,INSULIN therapy ,TYPE 2 diabetes ,HYPERGLYCEMIA ,HEALTH behavior ,COMPARATIVE studies ,CELIAC disease - Abstract
OBJECTIVE: To describe rescue insulin use and associated factors in the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE). RESEARCH DESIGN AND METHODS: GRADE participants (type 2 diabetes duration <10 years, baseline A1C 6.8%–8.5% on metformin monotherapy, N = 5,047) were randomly assigned to insulin glargine U-100, glimepiride, liraglutide, or sitagliptin and followed quarterly for a mean of 5 years. Rescue insulin (glargine or aspart) was to be started within 6 weeks of A1C >7.5%, confirmed. Reasons for delaying rescue insulin were reported by staff-completed survey. RESULTS: Nearly one-half of GRADE participants (N = 2,387 [47.3%]) met the threshold for rescue insulin. Among participants assigned to glimepiride, liraglutide, or sitagliptin, rescue glargine was added by 69% (39% within 6 weeks). Rescue aspart was added by 44% of glargine-assigned participants (19% within 6 weeks) and by 30% of non-glargine-assigned participants (14% within 6 weeks). Higher A1C values were associated with adding rescue insulin. Intention to change health behaviors (diet/lifestyle, adherence to current treatment) and not wanting to take insulin were among the most common reasons reported for not adding rescue insulin within 6 weeks. CONCLUSIONS: Proportionately, rescue glargine, when required, was more often used than rescue aspart, and higher A1C values were associated with greater rescue insulin use. Wanting to use noninsulin strategies to improve glycemia was commonly reported, although multiple factors likely contributed to not using rescue insulin. These findings highlight the persistent challenge of intensifying type 2 diabetes treatment with insulin, even in a clinical trial. [ABSTRACT FROM AUTHOR]
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- 2024
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4. The Use of Rescue Insulin in the Glycemia Reduction Approaches in Diabetes (GRADE) Study
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A Hollander, Priscilla, primary, Krause-Steinrauf, Heidi, primary, Butera, Nicole M., primary, Kazemi, Erin J., primary, Ahmann, Andrew J., primary, N Fattaleh, Basma, primary, Johnson, Mary L., primary, Killean, Tina, primary, S Lagari, Violet, primary, Larkin, Mary E., primary, A Legowski, Elizabeth, primary, Rasouli, Neda, primary, J Willis, Holly, primary, and Martin, Catherine L., primary
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- 2023
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5. Metacognitive Scaffolds Improve Self-Judgments of Accuracy in a Medical Intelligent Tutoring System
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Feyzi-Behnagh, Reza, Azevedo, Roger, and Legowski, Elizabeth
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In this study, we examined the effect of two metacognitive scaffolds on the accuracy of confidence judgments made while diagnosing dermatopathology slides in SlideTutor. Thirty-one (N = 31) first- to fourth-year pathology and dermatology residents were randomly assigned to one of the two scaffolding conditions. The cases used in this study were selected from the domain of nodular and diffuse dermatitides. Both groups worked with a version of SlideTutor that provided immediate feedback on their actions for 2 h before proceeding to solve cases in either the "Considering Alternatives" or "Playback" condition. No immediate feedback was provided on actions performed by participants in the scaffolding mode. Measurements included learning gains (pre-test and post-test), as well as metacognitive performance, including Goodman-Kruskal Gamma correlation, bias, and discrimination. Results showed that participants in both conditions improved significantly in terms of their diagnostic scores from pre-test to post-test. More importantly, participants in the Considering Alternatives condition outperformed those in the "Playback" condition in the accuracy of their confidence judgments and the discrimination of the correctness of their assertions while solving cases. The results suggested that presenting participants with their diagnostic decision paths and highlighting correct and incorrect paths helps them to become more metacognitively accurate in their confidence judgments.
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- 2014
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6. Use of a Medical ITS Improves Reporting Performance among Community Pathologists
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Crowley, Rebecca, Grzybicki, Dana, Legowski, Elizabeth, Wagner, Lynn, Castine, Melissa, Medvedeva, Olga, Tseytlin, Eugene, Jukic, Drazen, Raab, Stephen, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Aleven, Vincent, editor, Kay, Judy, editor, and Mostow, Jack, editor
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- 2010
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7. Automated Detection of Heuristics and Biases among Pathologists in a Computer-Based System
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Crowley, Rebecca S., Legowski, Elizabeth, and Medvedeva, Olga
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The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to diagnostic errors. The authors conducted the study using a computer-based system to view and diagnose virtual slide cases. The software recorded participant responses throughout the diagnostic process, and automatically classified participant actions based on definitions of eight common heuristics and/or biases. The authors measured frequency of heuristic use and bias across three levels of training. Biases studied were detected at varying frequencies, with availability and search satisficing observed most frequently. There were few significant differences by level of training. For representativeness and anchoring, the heuristic was used appropriately as often or more often than it was used in biased judgment. Approximately half of the diagnostic errors were associated with one or more biases. We conclude that heuristic use and biases were observed among physicians at all levels of training using the virtual slide system, although their frequencies varied. The system can be employed to detect heuristic use and to test methods for decreasing diagnostic errors resulting from cognitive biases.
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- 2013
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8. A Natural Language Intelligent Tutoring System for Training Pathologists: Implementation and Evaluation
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El Saadawi, Gilan M., Tseytlin, Eugene, and Legowski, Elizabeth
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Introduction: We developed and evaluated a Natural Language Interface (NLI) for an Intelligent Tutoring System (ITS) in Diagnostic Pathology. The system teaches residents to examine pathologic slides and write accurate pathology reports while providing immediate feedback on errors they make in their slide review and diagnostic reports. Residents can ask for help at any point in the case, and will receive context-specific feedback. Research questions: We evaluated (1) the performance of our natural language system, (2) the effect of the system on learning (3) the effect of feedback timing on learning gains and (4) the effect of ReportTutor on performance to self-assessment correlations. Methods: The study uses a crossover 2 x 2 factorial design. We recruited 20 subjects from 4 academic programs. Subjects were randomly assigned to one of the four conditions--two conditions for the immediate interface, and two for the delayed interface. An expert dermatopathologist created a reference standard and 2 board certified AP/CP pathology fellows manually coded the residents' assessment reports. Subjects were given the opportunity to self grade their performance and we used a survey to determine student response to both interfaces. Results: Our results show a highly significant improvement in report writing after one tutoring session with 4-fold increase in the learning gains with both interfaces but no effect of feedback timing on performance gains. Residents who used the immediate feedback interface first experienced a feature learning gain that is correlated with the number of cases they viewed. There was no correlation between performance and self-assessment in either condition.
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- 2008
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9. Islet Autoimmunity is Highly Prevalent and Associated With Diminished β-Cell Function in Patients With Type 2 Diabetes in the Grade Study
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Brooks-Worrell, Barbara, Hampe, Christiane S., Hattery, Erica G., Palomino, Brenda, Zangeneh, Sahar Z., Utzschneider, Kristina, Kahn, Steven E., Larkin, Mary E., Johnson, Mary L., Mather, Kieren J., Younes, Naji, Rasouli, Neda, Desouza, Cyrus, Cohen, Robert M., Park, Jean Y., Florez, Hermes J., Valencia, Willy Marcos, Shojaie, Ali, Palmer, Jerry P., Balasubramanyam, Ashok, Crandall, Jill P., McKee, Melissa Diane, Brown-Friday, Janet, Xhori, Entila, Ballentine-Cargill, Keisha, Duran, Sally, Lukin, Jennifer, Beringher, Stephanie, Gonzalez de la Torre, Susana, Phillips, Lawrence, Burgess, Elizabeth, Olson, Darin, Rhee, Mary, Wilson, Peter, Raines, Tasha Stephanie, Costello, Julie, Gullett, Chona, Maher-Albertelli, Maxine, Morehead, Folayan, Mungara, Radhika, Person, Saranjit, Savoye, Louise, Sibymon, Mabil, Tanukonda, Sridhar, White, Carol Ann, Holloway, Leah, Adams, Cynthia, Ross, April, Gonzalez Hattery, Erica, Gaba, Ruchi, Montes, Graciela, Wright, Charlyne, Hollander, Priscilla, Roe, Erin, Uy, Analyn, Burt, Polly, Estrada, Lorie, Chionh, Kris, Ismail-Beigi, Faramarz, Falck-Ytter, Corinna, Sayyed Kassem, Laure, Sood, Ajay, Tiktin, Margaret, Cramer, Bethany, Iacoboni, Jacalyn, Kononets, Maria V., Kulow, Tanya, Newman, Cynthia, Stancil, Katherine A., Sanders, Cristina, Tucker, Lisa, Werner, Amanda, Krol, Adrienne, McPhee, Gloria, Patel, Christine, Colosimo, Linda, Goland, Robin, Pring, James, Kringas, Patricia, Tejada, Jessica, Hausheer, Camille, Schneier, Harvey, Gumpel, Kelly, Kirpitch, Amanda, Green, Jennifer B., AbouAssi, Hiba, Chatterjee, Ranee, Feinglos, Mark N., English Jones, Jennifer, Khan, Shubi A., Kimpel, Jeanne B., Zimmer, Ronna P., Furst, Mary, Satterwhite, Barbara M., Thacker, Connie, Evans Kreider, Kathryn, Lteif, Amale, Hamilton, Tonya, Patel, Nick, Riera, Gabriela, Jackson, Marcia, Pirics, Vivian, Howard, Devin, Aguillar, Danielle, Hurt, Sloan, Bergenstal, Richard, Carlson, Anders, Martens, Thomas, Johnson, Mary, Hill, Renae, Hyatt, Jamie, Jensen, Connie, Madden, Marcia, Martin, Dianna, Willis, Holly, Konerza, Wanda, Passi, Rebecca, Kleeberger, Kathleen, Fortmann, Stephen, Herson, Michael, Mularski, Karen, Glauber, Harry, Prihoda, James, Ash, Britt, Carlson, Christina, Ramey, Phyllis Anne, Schield, Emily, Torgrimson-Ojerio, Britta, Arnold, Kathy, Kauffman, Bryan, Panos, Elease, Sahnow, Samantha, Bays, Kristi, Cook, Jennifer, Gluth, Jennifer, Sasaki, Debra, Schell, Katrina, Criscola, Jennifer, Friason, Camille, Jones, Suzi, Nazarov, Sergey, Barzilay, Joshua, Rassouli, Negah, Puttnam, Rachel, Curtis, Michelle, Stokes, Kia, Hollis, Bonita, Sanders-Jones, Cynthia, Nelson, Roslin, El-Haqq, Zakiah, Kolli, Abby, Tran, Tu, Wexler, Deborah, Larkin, Mary, Meigs, James, Dushkin, Amy, Rocchio, Gianna, Chambers, Brittany, Yepes, Mike, Steiner, Barbara, Dulin, Hilary, Cayford, Melody, DeManbey, Andrea, Gurry, Lindsey, Hillard, Mallory, Martin, Kimberly, Stevens, Christine, Thangthaeng, Nopporn, Kochis, Raquel, Raymond, Elyse, Ripley, Valerie, Park, Jean, Aroda, Vanita, Ghazi, Adline, Loveland, Amy, Hurtado, Maria, Kuhn, Alexander, Mofor, Florence, Marks, Jennifer, Oropesa-Gonzalez, Lisset, Riccio Veliz, Ana K., Nieto-Martinez, Ramfis, Gutt, Miriam, Ahmann, Andrew, Aby-Daniel, Diana, Joarder, Farahnaz, Morimoto, Victoria, Sprague, Carol, Yamashita, Daisuke, Cady, Nancy, Kirchhoff, Patricia, Rivera-Eschright, Nadia, Adducci, Joseph, Morales Gomez, Brianna, Goncharova, Alina, Hox, Sophia H., Petrovitch, Helen, Matwichyna, Michael, Jenkins, Victoria, Bermudez, Nina O., Ishii, Renée R., Hsia, Daniel S., Cefalu, William T., Greenway, Frank L., Waguespack, Celeste, King, Erin, Haynes, Natalie, Thomassie, Amy, Bourgeois, Brandi, Hazlett, Claire, Henry, Robert, Mudaliar, Sunder, Boeder, Schafer, Pettus, Jeremy, Diaz, Elsa, DeLue, Catherine, Castro, Erick, Hernandez, Sylvia, Krakoff, Jonathan, Curtis, Jeffrey M., Killean, Tina, Joshevama, Erica, Diaz, Enrique, Martin, Denelle, Karshner, Tracey, Albu, Jeanine, Pi-Sunyer, F. Xavier, Frances, Sylvaine, Maggio, Carol, Ellis, Emily, Bastawrose, Joseph, Gong, Xiuqun, Banerji, Mary Ann, August, Phyllis, Lorber, Daniel, Brown, Necole M., Josephson, Debra H., Thomas, Lorraine L., Tsovian, Mari, Cherian, Ajini, Jacobson, Marlo H., Mishko, Motria M., Kirkman, M. Sue, Bergamo, Katherine, Buse, John B., Dostou, Jean, Young, Laura, Goley, April, Kerr, Jeffrey, Largay, Joseph F., Guarda, Sonia, Cuffee, Juanita, Culmer, Dawn, Fraser, Rachael, Almeida, Hope, Coffer, Samantha, Debnam, Elizabeth, Kiker, Lauren, Morton, Sarah, Josey, Kim, Fuller, Gail, Garvey, W. Timothy, Cherrington, Andrea, Golson, Dana, Griffith, Olivia, Robertson, Mary Catherine, Agne, April, McCullars, Steve, Craig, Jacqueline, Kersey, Kimberly, Rogge, M. Colleen, Wilson, Carla, Burton, Kathryn, Lipp, Sonia, Vonder Meulen, Mary Beth, Schroeder, Emily, Steiner, Stephanie, Baker, Chelsea, Underkofler, Chantal, Douglass, Sara, Sivitz, William, Cline, Erin, Knosp, Laura, McConnell, Jennifer, Lowe, Tamara, Herman, William H., Pop-Busui, Rodica, Tan, Meng H., Martin, Catherine, Waltje, Andrea, Goodhall, Lynn, Eggleston, Rebecca, Kuo, Shihchen, Bule, Stephanie, Kessler, Nancy, LaSalle, Elizabeth, Seaquist, Elizabeth R., Bantle, Anne, Kumar, Anjali, Redmon, Bruce, Bantle, John, Harindhanavudhi, Tasma, Coe, Mary, Mech, Michael, Taddese, Abdisa, Lesne, Lesia, Smith, Shannon, Kuechenmeister, Lisa, Shivaswamy, Vijay, Morales, Ana Laura, Rodriguez, Maria Grace, Seipel, Kris, Alfred, Alissa, Eggert, Jenna, Lord, Grace, Taylor, William, Tillson, Renee, Schade, David S., Adolphe, Allen, Burge, Mark, Duran-Valdez, Elizabeth, Martinez, Janae, Hernandez McGinnis, Doris, Pucchetti, Benjamin, Scripsick, Elizabeth, DeFronzo, Ralph A., Cersosimo, Eugenio, Abdul-Ghani, Muhammad, Triplitt, Curtis, Verastiqui, Hector, Garza, Rosa Irene, Wright, Kathryn, Puckett, Curtiss, Raskin, Philip, Rhee, Chanhaeng, Abraham, Soma, Jordan, Lin Fan, Sao, Serey, Morton, Luisa, Smith, Oralenda, Osornio Walker, Laura, Schnurr-Breen, Laura, Ayala, Rosa, Kraymer, Robert, Sturgess, Daytheon, Utzschneider, Kristina M., Alarcon-Casas Wright, Lorena, Boyko, Edward, Tsai, Elaine C., Trence, Dace L., Fattaleh, Basma N., Montgomery, Brenda K., Atkinson, Karen M., Concepcion, Tessa, Kozedub, Alexandra, Moak, Cameron, Rhothisen, Samantha, Elasy, Tom A., Martin, Stephanie, Shackelford, Laura, Goidel, Rita, Hinkle, Nina, Lipps Hogan, Janie, Lovell, Cynthia, Myers, Janet, McGill, Janet B., Salam, Maamoun, Kissel, Sarah, Schweiger, Toni, Recklein, Carol, Tamborlane, William, Gatcomb, Patricia, Camp, Anne, Gulanski, Barbara, Inzucchi, Silvio, Pham, Kim, Alguard, Michele, Lessard, Katarzyna, Perez, Magalys, Magenheimer, Elizabeth, Montoza, Abmaridel, Nathan, David M., Lachin, John, Krause-Steinrauf, Heidi, Burch, Henry, Linder, Barbara, Bremer, Andrew, Backman, Michael, Bebu, Ionut, Buys, C.J., Fagan Murphy, Anna, Gao, Yuping, Gramzinski, Michaela, Hall, Stephanie, Legowski, Elizabeth, Arey, Alyssa, Bethepu, Joel, Lund, Claire, Mangat Dhaliwal, Pam, McGee, Paula, Mesimer, Emily, Ngo, Lisa, Steffes, Michael, Seegmiller, Jesse, Saenger, Amy, Arends, Valerie, Gabrielson, Deanna, Conner, Todd, Stuart, Warren, Day, Jolene, Scrymgeour, Alexandra, Soliman, Elsayed Z., Zhang, Zhu-Ming, Campbell, Charles, Hu, Julie, Keasler, Lisa, Hensley, Susan, Li, Yabing, Herman, William, Mihalcea, Rada, Perez-Rosas, Veronica, Prosser, Lisa, Resnicow, Kenneth, Ye, Wen, Shao, Hui, Zhang, Ping, Luchsinger, Jose, Sanchez, Danurys, Burch, Henry B., Fradkin, Judith, Groessl, Erik, Chong, Helen, Hillery, Naomi, Abdouch, Ivan, Brantley, Paula, Broyles, Frances E., Canaris, Gay, Copeland, Paul, Craine, Jeri J., Fein, Warren L., Lee, Melissa S., Meiners, Rebecca, Meiners, Vaughn, O’Neal, Hollis, Park, James E., Sledge, Edward, Steppel-Resnick, Jeanne, Turchin, Alexander, Higgins, John, Fischer, Lawrence, Golden, Sherita, Gonzalez, Jeffrey, Naik, Aanand, Walker, Elizabeth, Doner Lotenberg, Lynne, Gallivan, Joanne M., Lim, Joanne, Tuncer, Diane M., and Behringer-Massera, Stephanie
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endocrine system diseases ,Diabetes Mellitus, Type 2 ,Endocrinology, Diabetes and Metabolism ,Smoke ,T-Lymphocytes ,Internal Medicine ,Humans ,Pathophysiology ,Fires - Abstract
Islet autoimmunity may contribute to β-cell dysfunction in type 2 diabetes (T2D). Its prevalence and clinical significance have not been rigorously determined. In this ancillary study to the Glycemia Reduction Approaches in Diabetes: A Comparative Effectiveness Study (GRADE), we investigated the prevalence of cellular and humoral islet autoimmunity in patients with T2D duration of 4.0 ± 3.0 years (HbA1c 7.5 ± 0.5% on metformin alone). We measured T-cell autoreactivity against islet proteins, islet autoantibodies against 65-kDa GAD antigen, IA-2, and zinc transporter-8, and β-cell function. Cellular islet autoimmunity was present in 41.3%, humoral islet autoimmunity in 13.5%, and both in 5.3%. β-Cell function calculated as incremental area under the curve of glucose from 0–120 min (iAUC-CG) and ΔC-peptide(0–30)/Δglucose(0–30) from an oral glucose tolerance test was lower among T-cell–positive (T+) than T-cell–negative (T−) individuals using two different adjustments for insulin sensitivity (iAUC-CG: 13.2% [95% CI 0.3, 24.4] or 11.4% [95% CI 0.4, 21.2] lower; ΔC-peptide[0–30]/Δglucose[0–30]: 19% [95% CI 3.1, 32.3] or 17.7% [95% CI 2.6, 30.5%] lower). T+ patients had 17% higher HbA1c (95% CI 0.07, 0.28) and 7.7 mg/dL higher fasting plasma glucose levels (95% CI 0.2, 15.3) than T− patients. We conclude that islet autoimmunity is much more prevalent in patients with T2D than previously reported. T-cell–mediated autoimmunity is associated with diminished β-cell function and worse glycemic control.
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- 2021
10. Effect of a limited-enforcement intelligent tutoring system in dermatopathology on student errors, goals and solution paths
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Payne, Velma L., Medvedeva, Olga, Legowski, Elizabeth, Castine, Melissa, Tseytlin, Eugene, Jukic, Drazen, and Crowley, Rebecca S.
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- 2009
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11. Factors affecting feeling-of-knowing in a medical intelligent tutoring system: the role of immediate feedback as a metacognitive scaffold
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El Saadawi, Gilan M., Azevedo, Roger, Castine, Melissa, Payne, Velma, Medvedeva, Olga, Tseytlin, Eugene, Legowski, Elizabeth, Jukic, Drazen, and Crowley, Rebecca S.
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- 2010
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12. Evaluation of an Intelligent Tutoring System in Pathology: Effects of External Representation on Performance Gains, Metacognition, and Acceptance
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Crowley, Rebecca S., Legowski, Elizabeth, Medvedeva, Olga, Tseytlin, Eugene, Roh, Ellen, and Jukic, Drazen
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- 2007
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13. Use of a Medical ITS Improves Reporting Performance among Community Pathologists
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Crowley, Rebecca, primary, Grzybicki, Dana, additional, Legowski, Elizabeth, additional, Wagner, Lynn, additional, Castine, Melissa, additional, Medvedeva, Olga, additional, Tseytlin, Eugene, additional, Jukic, Drazen, additional, and Raab, Stephen, additional
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- 2010
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14. DomainBuilder: the knowledge authoring system for SlideTutor Intelligent Tutoring system
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Tseytlin, Eugene, primary, Linkov, Faina, additional, Castine, Melissa, additional, Legowski, Elizabeth, additional, and Jacobson, Rebecca S., additional
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- 2018
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15. Perceptual analysis of the reading of dermatopathology virtual slides by pathology residents
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Mello-Thoms, Claudia, Mello, Carlos A.B., Medvedeva, Olga, Castine, Melissa, Legowski, Elizabeth, Gardner, Gregory, Tseytlin, Eugene, and Crowley, Rebecca
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Skin diseases -- Analysis ,Health - Abstract
* Context.--The process by which pathologists arrive at a given diagnosis--a combination of their slide exploration strategy, perceptual information gathering, and cognitive decision making--has not been thoroughly explored, and many questions remain unanswered. Objective.--To determine how pathology residents learn to diagnose inflammatory skin dermatoses, we contrasted the slide exploration strategy, perceptual capture of relevant histopathologic findings, and cognitive integration of identified features between 2 groups of residents, those who had and those who had not undergone their dermatopathology rotation. Design.--Residents read a case set of 20 virtual slides (10 depicting nodular and diffuse dermatitis and 10 depicting subepidermal vesicular dermatitis), using an in-house-developed interface. We recorded residents' reports of diagnostic findings, conjectured diagnostic hypotheses, and final (or differential) diagnosis for each case, and time stamped each interaction with the interface. We created search maps of residents' slide exploration strategy. Results.--No statistically significant differences were observed between the resident groups in the number of correctly or incorrectly reported diagnostic findings, but residents with dermatopathology training generated significantly more correct hypotheses (mean improvement of 88.5%) and correct diagnoses (70% of all correct diagnoses). Conclusions.--Two types of slide exploration strategy were identified for both groups: (1) a focused and efficient search, observed when the final diagnosis was correct; and (2) a more dispersed, time-consuming strategy, observed when the final diagnosis was incorrect. This difference was statistically significant, and it suggests that initial interpretation of a slide may bias further slide exploration. (Arch Pathol Lab Med. 2012; 136:551-562; doi: 10.5858/arpa.2010-0697-OA), Pathology is the gold standard in medical diagnosis, and the pathologist's decision has the power to uniquely determine the outcome of a given patient's treatment. However, interpretation of either glass [...]
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- 2012
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16. NOBLE – Flexible concept recognition for large-scale biomedical natural language processing
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Tseytlin, Eugene, primary, Mitchell, Kevin, additional, Legowski, Elizabeth, additional, Corrigan, Julia, additional, Chavan, Girish, additional, and Jacobson, Rebecca S., additional
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- 2016
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17. A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens
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Jacobson, Rebecca S., primary, Becich, Michael J., additional, Bollag, Roni J., additional, Chavan, Girish, additional, Corrigan, Julia, additional, Dhir, Rajiv, additional, Feldman, Michael D., additional, Gaudioso, Carmelo, additional, Legowski, Elizabeth, additional, Maihle, Nita J., additional, Mitchell, Kevin, additional, Murphy, Monica, additional, Sakthivel, Mayurapriyan, additional, Tseytlin, Eugene, additional, and Weaver, JoEllen, additional
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- 2015
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18. Needs Assessment for Research Use of High-Throughput Sequencing at a Large Academic Medical Center
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Geskin, Albert, primary, Legowski, Elizabeth, additional, Chakka, Anish, additional, Chandran, Uma R, additional, Barmada, M. Michael, additional, LaFramboise, William A., additional, Berg, Jeremy, additional, and Jacobson, Rebecca S., additional
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- 2015
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19. Factors affecting feeling-of-knowing in a medical intelligent tutoring system: the role of immediate feedback as a metacognitive scaffold
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El Saadawi, Gilan M, Azevedo, Roger, Castine, Melissa, Payne, Velma, Medvedeva, Olga, Tseytlin, Eugene, Legowski, Elizabeth, Jukic, Drazen, Crowley, Rebecca S, El Saadawi, Gilan M, Azevedo, Roger, Castine, Melissa, Payne, Velma, Medvedeva, Olga, Tseytlin, Eugene, Legowski, Elizabeth, Jukic, Drazen, and Crowley, Rebecca S
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- 2010
20. Effect of a limited-enforcement intelligent tutoring system in dermatopathology on student errors, goals and solution paths
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Payne, Velma L, Medvedeva, Olga, Legowski, Elizabeth, Castine, Melissa, Tseytlin, Eugene, Jukic, Drazen, Crowley, Rebecca S, Payne, Velma L, Medvedeva, Olga, Legowski, Elizabeth, Castine, Melissa, Tseytlin, Eugene, Jukic, Drazen, and Crowley, Rebecca S
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- 2009
21. Metacognitive scaffolds improve self-judgments of accuracy in a medical intelligent tutoring system
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Feyzi-Behnagh, Reza, primary, Azevedo, Roger, additional, Legowski, Elizabeth, additional, Reitmeyer, Kayse, additional, Tseytlin, Eugene, additional, and Crowley, Rebecca S., additional
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- 2013
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22. Is grandma like alichen planus? The problem of image perception and knowledge retention in pathology
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Mello-Thoms, Claudia, primary, Legowski, Elizabeth, additional, and Tseytlin, Eugene, additional
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- 2013
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23. Automated detection of heuristics and biases among pathologists in a computer-based system
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Crowley, Rebecca S., primary, Legowski, Elizabeth, additional, Medvedeva, Olga, additional, Reitmeyer, Kayse, additional, Tseytlin, Eugene, additional, Castine, Melissa, additional, Jukic, Drazen, additional, and Mello-Thoms, Claudia, additional
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- 2012
- Full Text
- View/download PDF
24. Implementation and evaluation of a negation tagger in a pipeline-based system for information extract from pathology reports.
- Author
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Mitchell, Kevin J, Becich, Michael J, Berman, Jules J, Chapman, Wendy W, Gilbertson, John, Gupta, Dilip, Harrison, James, Legowski, Elizabeth, Crowley, Rebecca S, Mitchell, Kevin J, Becich, Michael J, Berman, Jules J, Chapman, Wendy W, Gilbertson, John, Gupta, Dilip, Harrison, James, Legowski, Elizabeth, and Crowley, Rebecca S
- Abstract
We have developed a pipeline-based system for automated annotation of Surgical Pathology Reports with UMLS terms that builds on GATE--an open-source architecture for language engineering. The system includes a module for detecting and annotating negated concepts, which implements the NegEx algorithm--an algorithm originally described for use in discharge summaries and radiology reports. We describe the implementation of the system, and early evaluation of the Negation Tagger. Our results are encouraging. In the key Final Diagnosis section, with almost no modification of the algorithm or phrase lists, the system performs with precision of 0.84 and recall of 0.80 against a gold-standard corpus of negation annotations, created by modified Delphi technique by a panel of pathologists. Further work will focus on refining the Negation Tagger and UMLS Tagger and adding additional processing resources for annotating free-text pathology reports.
- Published
- 2004
25. A natural language intelligent tutoring system for training pathologists: implementation and evaluation
- Author
-
El Saadawi, Gilan M., primary, Tseytlin, Eugene, additional, Legowski, Elizabeth, additional, Jukic, Drazen, additional, Castine, Melissa, additional, Fine, Jeffrey, additional, Gormley, Robert, additional, and Crowley, Rebecca S., additional
- Published
- 2007
- Full Text
- View/download PDF
26. Is grandma like a lichen planus? The problem of image perception and knowledge retention in pathology
- Author
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Abbey, Craig K., Mello-Thoms, Claudia R., Mello-Thoms, Claudia, Legowski, Elizabeth, and Tseytlin, Eugene
- Published
- 2013
- Full Text
- View/download PDF
27. Artificial Intelligence in Education : A Machine-Generated Literature Overview
- Author
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Myint Swe Khine and Myint Swe Khine
- Subjects
- Educational technology, Education—Research
- Abstract
This comprehensive volume explores the possibilities, challenges and ethical considerations of Artificial Intelligence (AI) in education through a machine-generated literature review that examines emerging research trends and findings. Each chapter presents summaries of pre-defined topics and includes a human-written introduction by the book editor. It covers critical areas such as educational data mining, learning analytics, personalised learning, adaptive assessment, intelligent tutoring systems, as well as the ethical challenges of AI in education. This volume provides valuable insights for educators, researchers, policymakers and students seeking to understand the transformative potential of AI in education. It serves as a reference point for navigating the evolving landscape of AI-assisted learning and offers a glimpse into the future of education in an AI-driven world. The auto-summaries were generated by a recursive clustering algorithm using the Dimensions Auto-summariser from Digital Science. The editor of this book selected the SN content to be auto-summarised and decided the order of appearance. Please note that these are extractive auto-summaries, consisting of original sentences, but are not representative of the original paper, as we do not show the full length of the publication. Please note that only published SN content is represented here and that machine-generated books are still at an experimental stage.
- Published
- 2024
28. Adaptive Technologies for Training and Education
- Author
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Paula J. Durlach, Alan M. Lesgold, Paula J. Durlach, and Alan M. Lesgold
- Subjects
- Computer-assisted instruction, Assistive computer technology, Internet in education
- Abstract
This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less well defined or where student-system interactions are less structured, such as during scenario-based simulation and immersive serious games. In order to address how to expand the reach of adaptive training technology to these domains, leading experts in the field present their work in areas such as student modeling, pedagogical strategy, knowledge assessment, natural language processing and virtual human agents. Several approaches to designing adaptive technology are discussed for both traditional educational settings and professional training domains. This book will appeal to anyone concerned with educational and training technology at a professional level, including researchers, training systems developers and designers.
- Published
- 2012
29. Intelligent Tutoring Systems : 10th International Conference, ITS 2010, Pittsburgh, PA, USA, June 14-18, 2010, Proceedings, Part II
- Author
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Vincent Aleven, Judy Kay, Jack Mostow, Vincent Aleven, Judy Kay, and Jack Mostow
- Subjects
- Education—Data processing, User interfaces (Computer systems), Human-computer interaction, Multimedia systems, Social sciences—Data processing, Natural language processing (Computer science), Artificial intelligence
- Abstract
The 10th International Conference on Intelligent Tutoring Systems, ITS 2010, cont- ued the bi-annual series of top-flight international conferences on the use of advanced educational technologies that are adaptive to users or groups of users. These highly interdisciplinary conferences bring together researchers in the learning sciences, computer science, cognitive or educational psychology, cognitive science, artificial intelligence, machine learning, and linguistics. The theme of the ITS 2010 conference was Bridges to Learning, a theme that connects the scientific content of the conf- ence and the geography of Pittsburgh, the host city. The conference addressed the use of advanced technologies as bridges for learners and facilitators of robust learning outcomes. We received a total of 186 submissions from 26 countries on 5 continents: Aust- lia, Brazil, Canada, China, Estonia, France, Georgia, Germany, Greece, India, Italy, Japan, Korea, Mexico, The Netherlands, New Zealand, Pakistan, Philippines, Saudi Arabia, Singapore, Slovakia, Spain, Thailand, Turkey, the UK and USA. We accepted 61 full papers (38%) and 58 short papers. The diversity of the field is reflected in the range of topics represented by the papers submitted, selected by the authors.
- Published
- 2010
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