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1. TransONet: Automatic Segmentation of Vasculature in Computed Tomographic Angiograms Using Deep Learning

Author

Rajeoni, Alireza Bagheri, Pederson, Breanna, Firooz, Ali, Abdollahi, Hamed, Smith, Andrew K., Clair, Daniel G., Lessner, Susan M., and Valafar, Homayoun

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, I.4.6
Abstract

Pathological alterations in the human vascular system underlie many chronic diseases, such as atherosclerosis and aneurysms. However, manually analyzing diagnostic images of the vascular system, such as computed tomographic angiograms (CTAs) is a time-consuming and tedious process. To address this issue, we propose a deep learning model to segment the vascular system in CTA images of patients undergoing surgery for peripheral arterial disease (PAD). Our study focused on accurately segmenting the vascular system (1) from the descending thoracic aorta to the iliac bifurcation and (2) from the descending thoracic aorta to the knees in CTA images using deep learning techniques. Our approach achieved average Dice accuracies of 93.5% and 80.64% in test dataset for (1) and (2), respectively, highlighting its high accuracy and potential clinical utility. These findings demonstrate the use of deep learning techniques as a valuable tool for medical professionals to analyze the health of the vascular system efficiently and accurately. Please visit the GitHub page for this paper at https://github.com/pip-alireza/TransOnet., Comment: Accepted for the 2023 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, USA

Published
2023

4. Risk Factors of COVID-19 Associated Mucormycosis (CAM) in Iranian Patients: A Single-Center Retrospective Study

Author

Tavakolpour, Soheil, Irani, Shirin, Yekaninejad, Mir Saeed, Alimardi, Masoud, Hasibi, Mehrdad, Abdollahi, Hamed, Kazemi, Mohammad Ali, Lotfi, Maryam, Shahbazian, Haneyeh, Nazemian Yazdi, Nader Ali, Samimiardestani, Seyedhadi, Firouzifar, Mohammadreza, Farahbakhsh, Farbod, Mirzaee Goodarzi, Mohammadreza, Feiz, Firoozeh, and Salehinia, Farahnaz

Published
2022
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7. SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Author

Neale, Benjamin M., Daly, Mark, Ganna, Andrea, Stevens, Christine, Pathak, Gita A., Andrews, Shea J., Kanai, Masahiro, Cordioli, Mattia, Karjalainen, Juha, Polimanti, Renato, Pirinen, Matti, Harerimana, Nadia, Veerapen, Kumar, Wolford, Brooke, Nguyen, Huy, Solomonson, Matthew, Liao, Rachel G., Chwialkowska, Karolina, Trankiem, Amy, Balaconis, Mary K., Hayward, Caroline, Richmond, Anne, Campbell, Archie, Morris, Marcela, Fawns-Ritchie, Chloe, Glessner, Joseph T., Shaw, Douglas M., Chang, Xiao, Polikowski, Hannah, Lauren, Petty E., Chen, Hung-Hsin, Wanying, Zhu, Hakonarson, Hakon, Porteous, David J., Below, Jennifer, North, Kari, McCormick, Joseph B., Timmers, Paul R.H.J., Wilson, James F., Tenesa, Albert, D’Mellow, Kenton, Kerr, Shona M., Niemi, Mari E.K., Nkambul, Lindokuhle, Aprile von Hohenstaufen, Kathrin, Sobh, Ali, Eltoukhy, Madonna M., Yassen, Amr M., Hegazy, Mohamed A.F., Okasha, Kamal, Eid, Mohammed A., Moahmed, Hanteera S., Shahin, Doaa, El-Sherbiny, Yasser M., Elhadidy, Tamer A., Abd Elghafar, Mohamed S., El-Jawhari, Jehan J., Mohamed, Attia A.S., Elnagdy, Marwa H., Samir, Amr, Abdel-Aziz, Mahmoud, Khafaga, Walid T., El-Lawaty, Walaa M., Torky, Mohamed S., El-shanshory, Mohamed R., Batini, Chiara, Lee, Paul H., Shrine, Nick, Williams, Alexander T., Tobin, Martin D., Guyatt, Anna L., John, Catherine, Packer, Richard J., Ali, Altaf, Free, Robert C., Wang, Xueyang, Wain, Louise V., Hollox, Edward J., Venn, Laura D., Bee, Catherine E., Adams, Emma L., Niavarani, Ahmadreza, Sharififard, Bahareh, Aliannejad, Rasoul, Amirsavadkouhi, Ali, Naderpour, Zeinab, Tadi, Hengameh Ansari, Aleagha, Afshar Etemadi, Ahmadi, Saeideh, Mohseni Moghaddam, Seyed Behrooz, Adamsara, Alireza, Saeedi, Morteza, Abdollahi, Hamed, Hosseini, Abdolmajid, Chariyavilaskul, Pajaree, Chamnanphon, Monpat, Suttichet, Thitima B., Shotelersuk, Vorasuk, Pongpanich, Monnat, Phokaew, Chureerat, Chetruengchai, Wanna, Jantarabenjakul, Watsamon, Putchareon, Opass, Torvorapanit, Pattama, Puthanakit, Thanyawee, Suchartlikitwong, Pintip, Hirankarn, Nattiya, Nilaratanakul, Voraphoj, Sodsai, Pimpayao, Brumpton, Ben M., Hveem, Kristian, Willer, Cristen, Zhou, Wei, Rogne, Tormod, Solligard, Erik, Åsvold, Bjørn Olav, Abedalthagafi, Malak, Alaamery, Manal, Alqahtani, Saleh, Baraka, Dona, Al Harthi, Fawz, Alsolm, Ebtehal, Safieh, Leen Abu, Alowayn, Albandary M., Alqubaishi, Fatimah, Al Mutairi, Amal, Mangul, Serghei, Alshareef, Abdulraheem, Sawaji, Mona, Almutairi, Mansour, Aljawini, Nora, Albesher, Nour, Arabi, Yaseen M., Mahmoud, Ebrahim S., Khattab, Amin K., Halawani, Roaa T., Alahmadey, Ziab Z., Albakri, Jehad K., Felemban, Walaa A., Suliman, Bandar A., Hasanato, Rana, Al-Awdah, Laila, Alghamdi, Jahad, AlZahrani, Deema, AlJohani, Sameera, Al-Afghani, Hani, Alrashed, May, AlDhawi, Nouf, AlBardis, Hadeel, Alkwai, Sarah, Alswailm, Moneera, Almalki, Faisal, Albeladi, Maha, Almohammed, Iman, Barhoush, Eman, Albader, Anoud, Massadeh, Salam, AlMalik, Abdulaziz, Alotaibi, Sara, Alghamdi, Bader, Jung, Junghyun, Fawzy, Mohammad S., Lee, Yunsung, Magnus, Per, Trogstad, Lill-Iren S., Helgeland, Øyvind, Harris, Jennifer R., Mangino, Massimo, Spector, Tim D., Emma, Duncan, Smieszek, Sandra P., Przychodzen, Bartlomiej P., Polymeropoulos, Christos, Polymeropoulos, Vasilios, Polymeropoulos, Mihael H., Fernandez-Cadenas, Israel, Perez-Tur, Jordi, Llucià-Carol, Laia, Cullell, Natalia, Muiño, Elena, Cárcel-Márquez, Jara, DeDiego, Marta L., Iglesias, Lara Lloret, Planas, Anna M., Soriano, Alex, Rico, Veronica, Agüero, Daiana, Bedini, Josep L., Lozano, Francisco, Domingo, Carlos, Robles, Veronica, Ruiz-Jaén, Francisca, Márquez, Leonardo, Gomez, Juan, Coto, Eliecer, Albaiceta, Guillermo M., García-Clemente, Marta, Dalmau, David, Arranz, Maria J., Dietl, Beatriz, Serra-Llovich, Alex, Soler, Pere, Colobrán, Roger, Martín-Nalda, Andrea, Martínez, Alba Parra, Bernardo, David, Rojo, Silvia, Fiz-López, Aida, Arribas, Elisa, Cal-Sabater, Paloma de la, Segura, Tomás, González-Villa, Esther, Serrano-Heras, Gemma, Martí-Fàbregas, Joan, Jiménez-Xarrié, Elena, de Felipe Mimbrera, Alicia, Masjuan, Jaime, García-Madrona, Sebastian, Domínguez-Mayoral, Anna, Villalonga, Joan Montaner, Menéndez-Valladares, Paloma, Chasman, Daniel I., Buring, Julie E., Ridker, Paul M., Franco, Giulianini, Sesso, Howard D., Manson, JoAnn E., Glessner, Joseph R., Medina-Gomez, Carolina, Uitterlinden, Andre G., Ikram, M. Arfan, Kristiansson, Kati, Koskelainen, Sami, Perola, Markus, Donner, Kati, Kivinen, Katja, Palotie, Aarno, Ripatti, Samuli, Ruotsalainen, Sanni, Kaunisto, Mari, FinnGen, Nakanishi, Tomoko, Butler-Laporte, Guillaume, Forgetta, Vincenzo, Morrison, David R., Ghosh, Biswarup, Laurent, Laetitia, Belisle, Alexandre, Henry, Danielle, Abdullah, Tala, Adeleye, Olumide, Mamlouk, Noor, Kimchi, Nofar, Afrasiabi, Zaman, Branka Vulesevic, Nardin Rezk, Bouab, Meriem, Guzman, Charlotte, Petitjean, Louis, Tselios, Chris, Xue, Xiaoqing, Schurr, Erwin, Afilalo, Jonathan, Afilalo, Marc, Oliveira, Maureen, Brenner, Bluma, Lepage, Pierre, Ragoussis, Jiannis, Auld, Daniel, Brassard, Nathalie, Durand, Madeleine, Chassé, Michaël, Kaufmann, Daniel E., Lathrop, G. Mark, Mooser, Vincent, Richards, J. Brent, Li, Rui, Adra, Darin, Rahmouni, Souad, Georges, Michel, Moutschen, Michel, Misset, Benoit, Darcis, Gilles, Guiot, Julien, Guntz, Julien, Azarzar, Samira, Gofflot, Stéphanie, Beguin, Yves, Claassen, Sabine, Malaise, Olivier, Huynen, Pascale, Meuris, Christelle, Thys, Marie, Jacques, Jessica, Léonard, Philippe, Frippiat, Frederic, Giot, Jean-Baptiste, Sauvage, Anne-Sophie, Von Frenckell, Christian, Belhaj, Yasmine, Lambermont, Bernard, Pigazzini, Sara, Nkambule, Lindokuhle, Daya, Michelle, Shortt, Jonathan, Rafaels, Nicholas, Wicks, Stephen J., Crooks, Kristy, Barnes, Kathleen C., Gignoux, Christopher R., Chavan, Sameer, Laisk, Triin, Läll, Kristi, Lepamets, Maarja, Mägi, Reedik, Esko, Tõnu, Reimann, Ene, Milani, Lili, Alavere, Helene, Metsalu, Kristjan, Puusepp, Mairo, Metspalu, Andres, Naaber, Paul, Laane, Edward, Pesukova, Jaana, Peterson, Pärt, Kisand, Kai, Tabri, Jekaterina, Allos, Raili, Hensen, Kati, Starkopf, Joel, Ringmets, Inge, Tamm, Anu, Kallaste, Anne, Bochud, Pierre-Yves, Rivolta, Carlo, Bibert, Stéphanie, Quinodoz, Mathieu, Kamdar, Dhryata, Boillat, Noémie, Nussle, Semira Gonseth, Albrich, Werner, Suh, Noémie, Neofytos, Dionysios, Erard, Véronique, Voide, Cathy, FHoGID, RegCOVID, P-PredictUs, SeroCOVID, CRiPSI, de Cid, Rafael, Galván-Femenía, Iván, Blay, Natalia, Carreras, Anna, Cortés, Beatriz, Farré, Xavier, Sumoy, Lauro, Moreno, Victor, Mercader, Josep Maria, Guindo-Martinez, Marta, Torrents, David, Kogevinas, Manolis, Garcia-Aymerich, Judith, Castaño-Vinyals, Gemma, Dobaño, Carlota, Renieri, Alessandra, Mari, Francesca, Fallerini, Chiara, Daga, Sergio, Benetti, Elisa, Baldassarri, Margherita, Fava, Francesca, Frullanti, Elisa, Valentino, Floriana, Doddato, Gabriella, Giliberti, Annarita, Tita, Rossella, Amitrano, Sara, Bruttini, Mirella, Croci, Susanna, Meloni, Ilaria, Mencarelli, Maria Antonietta, Lo Rizzo, Caterina, Pinto, Anna Maria, Beligni, Giada, Tommasi, Andrea, Di Sarno, Laura, Palmieri, Maria, Carriero, Miriam Lucia, Alaverdian, Diana, Busani, Stefano, Bruno, Raffaele, Vecchia, Marco, Belli, Mary Ann, Picchiotti, Nicola, Sanarico, Maurizio, Gori, Marco, Furini, Simone, Mantovani, Stefania, Ludovisi, Serena, Mondelli, Mario Umberto, Castelli, Francesco, Quiros-Roldan, Eugenia, Antoni, Melania Degli, Zanella, Isabella, Vaghi, Massimo, Rusconi, Stefano, Siano, Matteo, Montagnani, Francesca, Emiliozzi, Arianna, Fabbiani, Massimiliano, Rossetti, Barbara, Bargagli, Elena, Bergantini, Laura, D’Alessandro, Miriana, Cameli, Paolo, Bennett, David, Anedda, Federico, Marcantonio, Simona, Scolletta, Sabino, Franchi, Federico, Mazzei, Maria Antonietta, Guerrini, Susanna, Conticini, Edoardo, Cantarini, Luca, Frediani, Bruno, Tacconi, Danilo, Spertilli, Chiara, Feri, Marco, Donati, Alice, Scala, Raffaele, Guidelli, Luca, Spargi, Genni, Corridi, Marta, Nencioni, Cesira, Croci, Leonardo, Bandini, Maria, Caldarelli, Gian Piero, Piacentini, Paolo, Desanctis, Elena, Cappelli, Silvia, Canaccini, Anna, Verzuri, Agnese, Anemoli, Valentina, Ognibene, Agostino, Pancrazzi, Alessandro, Lorubbio, Maria, D’Arminio Monforte, Antonella, Miraglia, Federica Gaia, Girardis, Massimo, Venturelli, Sophie, Cossarizza, Andrea, Antinori, Andrea, Vergori, Alessandra, Gabrieli, Arianna, Riva, Agostino, Francisci, Daniela, Schiaroli, Elisabetta, Paciosi, Francesco, Scotton, Pier Giorgio, Andretta, Francesca, Panese, Sandro, Scaggiante, Renzo, Gatti, Francesca, Parisi, Saverio Giuseppe, Baratti, Stefano, Della Monica, Matteo, Piscopo, Carmelo, Capasso, Mario, Russo, Roberta, Andolfo, Immacolata, Iolascon, Achille, Fiorentino, Giuseppe, Carella, Massimo, Castori, Marco, Merla, Giuseppe, Squeo, Gabriella Maria, Aucella, Filippo, Raggi, Pamela, Marciano, Carmen, Perna, Rita, Bassetti, Matteo, Di Biagio, Antonio, Sanguinetti, Maurizio, Masucci, Luca, Valente, Serafina, Mandalà, Marco, Giorli, Alessia, Salerni, Lorenzo, Zucchi, Patrizia, Parravicini, Pierpaolo, Menatti, Elisabetta, Trotta, Tullio, Giannattasio, Ferdinando, Coiro, Gabriella, Lena, Fabio, Coviello, Domenico A., Mussini, Cristina, Martinelli, Enrico, Mancarella, Sandro, Tavecchia, Luisa, Crotti, Lia, Gabbi, Chiara, Rizzi, Marco, Maggiolo, Franco, Ripamonti, Diego, Bachetti, Tiziana, La Rovere, Maria Teresa, Sarzi-Braga, Simona, Bussotti, Maurizio, Ceri, Stefano, Pinoli, Pietro, Raimondi, Francesco, Biscarini, Filippo, Stella, Alessandra, Zguro, Kristina, Capitani, Katia, Suardi, Claudia, Dei, Simona, Parati, Gianfranco, Ravaglia, Sabrina, Artuso, Rosangela, Bottà, Giordano, Di Domenico, Paolo, Rancan, Ilaria, Francesco Bianchi, Antonio Perrella, Romani, Davide, Bergomi, Paola, Catena, Emanuele, Colombo, Riccardo, Tanfoni, Marco, Vincenti, Antonella, Ferri, Claudio, Grassi, Davide, Pessina, Gloria, Tumbarello, Mario, Di Pietro, Massimo, Sabrina, Ravaglia, Luchi, Sauro, Barbieri, Chiara, Acquilini, Donatella, Andreucci, Elena, Segala, Francesco Vladimiro, Tiseo, Giusy, Falcone, Marco, Lista, Mirjam, Poscente, Monica, De Vivo, Oreste, Petrocelli, Paola, Guarnaccia, Alessandra, Baroni, Silvia, Smith, Albert V., Boughton, Andrew P., Li, Kevin W., LeFaive, Jonathon, Annis, Aubrey, Justice, Anne E., Mirshahi, Tooraj, Chittoor, Geetha, Josyula, Navya Shilpa, Kosmicki, Jack A., Ferreira, Manuel A.R., Leader, Joseph B., Carey, Dave J., Gass, Matthew C., Horowitz, Julie E., Cantor, Michael N., Yadav, Ashish, Baras, Aris, Abecasis, Goncalo R., van Heel, David A., Hunt, Karen A., Mason, Dan, Huang, Qin Qin, Finer, Sarah, Genes & Health Research Team, Trivedi, Bhavi, Griffiths, Christopher J., Martin, Hilary C., Wright, John, Trembath, Richard C., Soranzo, Nicole, Zhao, Jing Hua, Butterworth, Adam S., Danesh, John, Di Angelantonio, Emanuele, Marike Boezen, Lude Franke, Deelen, Patrick, Claringbould, Annique, Lopera, Esteban, Warmerdam, Robert, Vonk, Judith.M., van Blokland, Irene, Lanting, Pauline, Ori, Anil P.S., Sebastian Zöllner, Brooke Wolford, Wang, Jiongming, Beck, Andrew, Peloso, Gina, Ho, Yuk-Lam, Sun, Yan V., Huffman, Jennifer E., O’Donnell, Christopher J., Cho, Kelly, Tsao, Phil, Gaziano, J. Michael, Nivard, Michel (M.G.), de geus, Eco (E.J.C.), Bartels, Meike, Hottenga, Jouke Jan, Weiss, Scott T., Karlson, Elizabeth W., Smoller, Jordan W., Green, Robert C., Anne Feng, Yen-Chen, Mercader, Josep, Murphy, Shawn N., Meigs, James B., Woolley, Ann E., Perez, Emma F., Rader, Daniel, Verma, Anurag, Ritchie, Marylyn D., Li, Binglan, Verma, Shefali S., Lucas, Anastasia, Bradford, Yuki, Zeberg, Hugo, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklos, Nkambul, Lindo, Tardif, Nicolas, Rooyackers, Olav, Grip, Jonathan, Maricic, Tomislav, Karczewski, Konrad J., Atkinson, Elizabeth G., Tsuo, Kristin, Baya, Nikolas, Turley, Patrick, Gupta, Rahul, Callier, Shawneequa, Walters, Raymond K., Palmer, Duncan S., Sarma, Gopal, Cheng, Nathan, Lu, Wenhan, Bryant, Sam, Churchhouse, Claire, Cusick, Caroline, Goldstein, Jacqueline I., King, Daniel, Seed, Cotton, Finucane, Hilary, Martin, Alicia R., Satterstrom, F. Kyle, Wilson, Daniel J., Armstrong, Jacob, Rudkin, Justine K., Band, Gavin, Earle, Sarah G., Lin, Shang-Kuan, Arning, Nicolas, Crook, Derrick W., Wyllie, David H., O’Connell, Anne Marie, Spencer, Chris C.A., Koelling, Nils, Caulfield, Mark J., Scott, Richard H., Fowler, Tom, Moutsianas, Loukas, Kousathanas, Athanasios, Pasko, Dorota, Walker, Susan, Rendon, Augusto, Stuckey, Alex, Odhams, Christopher A., Rhodes, Daniel, Chan, Georgia, Arumugam, Prabhu, Ball, Catherine A., Hong, Eurie L., Rand, Kristin, Girshick, Ahna, Guturu, Harendra, Baltzell, Asher Haug, Roberts, Genevieve, Park, Danny, Coignet, Marie, McCurdy, Shannon, Knight, Spencer, Partha, Raghavendran, Rhead, Brooke, Zhang, Miao, Berkowitz, Nathan, Gaddis, Michael, Noto, Keith, Ruiz, Luong, Pavlovic, Milos, Sloofman, Laura G., Charney, Alexander W., Beckmann, Noam D., Schadt, Eric E., Jordan, Daniel M., Thompson, Ryan C., Gettler, Kyle, Abul-Husn, Noura S., Ascolillo, Steven, Buxbaum, Joseph D., Chaudhary, Kumardeep, Cho, Judy H., Itan, Yuval, Kenny, Eimear E., Belbin, Gillian M., Sealfon, Stuart C., Sebra, Robert P., Salib, Irene, Collins, Brett L., Levy, Tess, Britvan, Bari, Keller, Katherine, Tang, Lara, Peruggia, Michael, Hiester, Liam L., Niblo, Kristi, Aksentijevich, Alexandra, Labkowsky, Alexander, Karp, Avromie, Zlatopolsky, Menachem, Preuss, Michael, Loos, Ruth J.F., Nadkarni, Girish N., Do, Ron, Hoggart, Clive, Choi, Sam, Underwood, Slayton J., O’Reilly, Paul, Huckins, Laura M., Zyndorf, Marissa, D’Antonio, Matteo, Nguyen, Jennifer P., Arthur, Timothy D., Matsui, Hiroko, D’Antonio-Chronowska, Agnieszka, and Frazer, Kelly A.

Published
2021
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9. Laparotomy Versus Laparoscopy Cholecystectomy for Surgical Treatment in Patients with Gallstone Disease: A Comparative Cost-Effectiveness Analysis.

Author

Dehcheshmeh, Nayeb Fadaei, Abdollahi, Hamed, Haghighizadeh, Mohammadhosein, and Faraji-Khiavi, Farzad

Subjects
*GALLSTONES, *LAPAROSCOPIC surgery, *TREE age, *ABDOMINAL surgery, *COST effectiveness, *CHOLECYSTECTOMY
Abstract

Background: Due to the increasing costs of the healthcare system and limited financial resources, healthcare policymakers should adopt more cost-effective strategies. Objectives: This study aimed to compare the cost-effectiveness of laparotomy cholecystectomy with laparoscopy. Methods: This economic evaluation was conducted on patients with cholecystitis who were candidates for surgery in a private hospital in Ahvaz in 2021. Data collection tools consisted of four parts: (1) demographic information checklist; (2) clinical information checklist; (3) cost checklist; and (4) effectiveness assessment tool. SPSS22 and STATA14.2 were used for data analysis. One-way sensitivity analysis and Tornado diagrams were performed using Tree Age software. Results: The mean total effectiveness score in patients treated with laparoscopy was 83.44 (SD = 11.34), which was higher than those treated with laparotomy at 68.39 (SD = 13.61). This difference was statistically significant in all effectiveness criteria, except for postoperative infection rates and length of operation (P < 0.001). The mean cost for patients undergoing laparoscopy was significantly higher than for those undergoing laparotomy ($481.43 vs. $459.49). However, overall, laparoscopic treatment (5.77) was more cost-effective than laparotomy (6.71). The laparoscopic procedure was approximately $1.47 per effectiveness unit cheaper than laparotomy, according to the ICER. One-way sensitivity analysis showed that the laparoscopic method remained more cost-effective, even when adjusting for cost and effectiveness components. Conclusions: Although laparoscopic cholecystectomy was more expensive than laparotomy cholecystectomy, it was generally more costeffective. The results of this research may assist Iran's healthcare policymakers and managers in promoting laparoscopic cholecystectomy in hospitals. [ABSTRACT FROM AUTHOR]

Published
2024

13. Integrating Omics Data and AI for Cancer Diagnosis and Prognosis.

Author

Ozaki, Yousaku, Broughton, Phil, Abdollahi, Hamed, Valafar, Homayoun, and Blenda, Anna V.

Subjects
TUMOR diagnosis, GENOMICS, ARTIFICIAL intelligence, RADIOMICS, EPIGENOMICS, GENE expression, PROTEOMICS, TUMORS, MACHINE learning
Abstract

Simple Summary: Cancer remains one of the leading causes of death worldwide, which emphasizes the need for its early and accurate diagnosis and prognosis. Our review explores AI's potential in this field, analyzing 89 recent studies from 2020 through 2023. Specifically, these studies included AI applications for the analysis of multi-omics data: radiomics, pathomics, clinical records, and lab data. Notably, eight studies combined diverse omics data types (genomics, transcriptomics, epigenomics, and proteomics). Integration of AI for the analysis of clinical and omics data contributes to a significant advancement and is essential for safe clinical implementation. Cancer is one of the leading causes of death, making timely diagnosis and prognosis very important. Utilization of AI (artificial intelligence) enables providers to organize and process patient data in a way that can lead to better overall outcomes. This review paper aims to look at the varying uses of AI for diagnosis and prognosis and clinical utility. PubMed and EBSCO databases were utilized for finding publications from 1 January 2020 to 22 December 2023. Articles were collected using key search terms such as "artificial intelligence" and "machine learning." Included in the collection were studies of the application of AI in determining cancer diagnosis and prognosis using multi-omics data, radiomics, pathomics, and clinical and laboratory data. The resulting 89 studies were categorized into eight sections based on the type of data utilized and then further subdivided into two subsections focusing on cancer diagnosis and prognosis, respectively. Eight studies integrated more than one form of omics, namely genomics, transcriptomics, epigenomics, and proteomics. Incorporating AI into cancer diagnosis and prognosis alongside omics and clinical data represents a significant advancement. Given the considerable potential of AI in this domain, ongoing prospective studies are essential to enhance algorithm interpretability and to ensure safe clinical integration. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Effect of vitamin B1 supplementation on blood creatinine and lactate levels and clinical outcomes in patients in intensive care units: a systematic review and meta-analysis of randomized controlled trials.

Author

Karimi, Elmira, Gholizadeh, Mohammad, Abdolahi, Mina, Sedighiyan, Mohsen, Salehinia, Farahnaz, Siri, Goli, Asanjarani, Behzad, Yousefi, Abolghasem, Gandomkar, Hossein, and Abdollahi, Hamed

Subjects
CREATININE, PATIENTS, THERAPEUTICS, RENAL replacement therapy, PLACEBOS, VITAMIN B1, HOSPITAL admission & discharge, TREATMENT effectiveness, META-analysis, HOSPITAL mortality, DESCRIPTIVE statistics, SYSTEMATIC reviews, MEDLINE, LACTATES, INTENSIVE care units, MEDICAL databases, ONLINE information services, LENGTH of stay in hospitals, MEDICAL screening, DIETARY supplements, EVALUATION
Abstract

Context The metabolic response to stress can deplete the remaining thiamine stores, leading to thiamine deficiency. Objective This study is the first meta-analysis of the effectiveness of thiamine supplementation on clinical and biochemical outcomes in adult patients admitted to the intensive care unit (ICU). Data Sources Scopus, PubMed, and Cochrane databases were searched to select studies up to 20 November 2022. Study Selection Studies investigating the effect of thiamine supplementation on serum lactate and creatinine levels, the need for renal replacement therapy, length of ICU stay, and mortality rate in ICU patients were selected. Data Extraction After excluding studies based on title and abstract screening, 2 independent investigators reviewed the full texts of the remaining articles. In the next step, a third investigator resolved any discrepancy in the article selection process. Results Of 1628 retrieved articles, 8 were selected for final analysis. This study showed that thiamine supplementation reduced the serum creatinine level (P =.03) compared with placebo. In addition, according to subgroup analysis, serum creatinine concentration was significantly lower in patients >60 years old (P < .00001). However, there was no statistically significant difference in the lactate level between the thiamine supplementation and placebo groups (P =.26). Thiamine supplementation did not decrease the risk of all-cause mortality (P =.71) or the need for renal replacement therapy (P =.14). The pooled results of eligible randomized controlled trials also showed that thiamine supplementation did not reduce the length of ICU stay in comparison to the placebo group (P =.39). Conclusion This meta-analysis provides evidence that thiamine supplementation has a protective effect against blood creatinine increase in ICU patients. However, further high-quality trials are needed to discover the effect of thiamine supplementation on clinical and biochemical outcomes in ICU patients. Systematic Review Registration PROSPERO no. CRD42023399710 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=399710). [ABSTRACT FROM AUTHOR]

Published
2024
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15. Effect of vitamin B1 supplementation on blood creatinine and lactate levels and clinical outcomes in patients in intensive care units: a systematic review and meta-analysis of randomized controlled trials

Author

Karimi, Elmira, primary, Gholizadeh, Mohammad, additional, Abdolahi, Mina, additional, Sedighiyan, Mohsen, additional, Salehinia, Farahnaz, additional, Siri, Goli, additional, Asanjarani, Behzad, additional, Yousefi, Abolghasem, additional, Gandomkar, Hossein, additional, and Abdollahi, Hamed, additional

Published
2023
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24. The relationship between cumulative dose of immunosuppressive agents and COVID‐19‐associated mucormycosis: A multicenter cross‐sectional study

Author

Rastkar, Mohsen, primary, SeyedAlinaghi, SeyedAhmad, additional, Asanjarani, Behzad, additional, Siri, Goli, additional, Abdollahi, Hamed, additional, Ghadami, Ladan, additional, Hasibi, Mehrdad, additional, Khodashahi, Rozita, additional, Bagheri, AmirBehzad, additional, and Asadollahi‐Amin, Ali, additional

Published
2022
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27. COVID-19-associated mucormycosis in Iran: A retrospective study on 52 patients

Author

Tavakolpour, Soheil, primary, Irani, Shirin, additional, Yekaninejad, Mir Saeed, additional, Alimardi, Masoud, additional, Hasibi, Mehrdad, additional, Abdollahi, Hamed, additional, Kazemi, Mohammad Ali, additional, Lotfi, Maryam, additional, Shahbazian, Haneyeh, additional, Yazdi, Nader Ali Nazemian, additional, Samimiardestani, Seyedhadi, additional, Firouzifar, Mohammadreza, additional, Farahbakhsh, Farbod, additional, Goodarzi, Mohammadreza Mirzaee, additional, Feiz, Firoozeh, additional, and Salehinia, Farahnaz, additional

Published
2022
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32. Omega‐3 polyunsaturated fatty acids supplementation improve clinical symptoms in patients with Covid‐19: A randomised clinical trial

Author

Sedighiyan, Mohsen, primary, Abdollahi, Hamed, additional, Karimi, Elmira, additional, Badeli, Mostafa, additional, Erfanian, Reza, additional, Raeesi, Shima, additional, Hashemi, Rezvan, additional, Vahabi, Zahra, additional, Asanjarani, Behzad, additional, Mansouri, Fariba, additional, and Abdolahi, Mina, additional

Published
2021
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34. Protracted COVID-19 during Treatment of Facial Palsy

Author

Hasibi, Mehrdad, Seyed Ahadi, Maral, Abdollahi, Hamed, and Jafari, Mehrdad

Subjects
Article Subject
Abstract

Neurologic manifestations are increasingly reported as the coronavirus disease 2019 (COVID-19) pandemic continues. This is a report of a COVID-19 patient with Bell's palsy. Case Summary. A 52-year-old man with fever and malaise was tested positive for COVID-19. After a week, he developed right-sided peripheral facial palsy and was treated with corticosteroids in conjunction with antiviral treatment which resulted in complete recovery. Discussion. Concomitant treatment of corticosteroids and antiviral treatment can decrease morbidity in patients with COVID-19-related Bell's palsy.

Published
2021
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35. Additional file 1 of The omega-3 and Nano-curcumin effects on vascular cell adhesion molecule (VCAM) in episodic migraine patients: a randomized clinical trial

Author

Abdolahi, Mina, Karimi, Elmira, Sarraf, Payam, Tafakhori, Abbas, Siri, Goli, Salehinia, Farahnaz, Sedighiyan, Mohsen, Asanjarani, Behzad, Badeli, Mostafa, Abdollahi, Hamed, Yoosefi, Niyoosha, yousefi, Abolghasem, rad, Amir Shayegan, and Djalali, Mahmoud

Abstract

Additional file 1: Figure S1. Flow chart for the clinical trial. This Flow chart shows the number of participants in the four study groups, the number of missing in every group as well as participants entered to the analysis.

Published
2021
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36. he omega-3 and Nano-curcumin effects on vascular cell adhesion molecule (VCAM) in episodic migraine patients: a randomized clinical trial

Author

Abdolahi, Mina, primary, Karimi, Elmira, additional, Sarraf, Payam, additional, Tafakhori, Abbas, additional, Siri, Goli, additional, Sedighiyan, Mohsen, additional, Asanjarani, Behzad, additional, Djalali, Mahmoud, additional, Badeli, Mostafa, additional, Abdollahi, Hamed, additional, Yoosefi, Niyoosha, additional, Abdullah, Hakima, additional, and Shayegan, Amir, additional

Published
2021
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44. Molecular identification and phylogenetic analysis of chronic bee paralysis virus in Iran

Author

Ghorani, Mohammadreza, Ghalyanchi Langeroudi, Arash, Madadgar, Omid, Rezapanah, Mohammadreza, Nabian, Sedigheh, Khaltabadi Farahani, Reza, Maghsoudloo, Hossein, Forsi, Mohammad, Abdollahi, Hamed, and Akbarein, Hesameddin

Subjects
animal structures, Phylogenetic analysis, animal diseases, viruses, embryonic structures, Honeybee, RT-PCR, Original Article, Chronic bee paralysis virus, Iran
Abstract

Chronic bee paralysis virus (CBPV) is an unclassified polymorphic single-stranded RNA virus. Among the viruses infecting honeybees, CBPV is known to induce significant losses in honeybee colonies. In this study, a total number of eighty-nine suspected apiaries from four regions of Iran (including Mazandaran, Khorasan Razavi, Hormozgan, and Kurdistan) were sampled and submitted for molecular identification. Three positive samples were detected by RT-PCR. All positive samples were confirmed by sequencing. The phylogenetic tree which displays the molecular relationship between the viruses of different Iranian geographic regions and references isolates was constructed. The Iranian isolates formed two distinct phylogenetic groups (Group 1 and Group 2). The IR-CPV-GMG-1, IR-CPV-GMG-2, IR-CPV-GMG-4, and IR-CPV-GMG-6 formed Group 1 and IR-CPV-GMG-3, IR-CPV-GMG-5, and IR-CPV-GMG-7 were in Group 2 as a distinct group. Iranian isolates in group 1 were similar to European and East Asian CBPVs. This research was the first phylogenetic analysis of CBPV in Iran. Further researches are needed to study the other aspects of this virus-like genetic characteristics and pathogenesis in Iran.

Published
2017

45. Protein interaction mapping interpretation of none alcoholic fatty liver disease model of rats after fat diet feeding

Author

Abdollahi, Hamed, Zamanian Azodi, Mona, and Hatami, Behzad

Subjects
None alcoholic fatty liver disease, Original Article, Centrality analysis, Gene ontology, Rat Model, Gene expression profile, Protein-protein interaction network analysis
Abstract

Aim: This study investigates the effect of fat diet on gene expression profile in rat liver via protein-protein interaction mapping analysis. Background: Nonalcoholic fatty liver disease (NAFLD) is a prevalent condition of liver in the world. This progressive metabolic disease is representative with fat accumulation in the patients’ liver that can led to advance stages, namely, cirrhosis and eventually cancer. Methods: Differentially expressed genes of NAFLD rat liver after 2, 4 and 6 weeks fat diet feeding were analyzed via GEO2R and protein-protein interaction network by Cytoscape v3.6.0. and the related plug-ins. The important genes were assigned based on degree and betweenness centrality analysis and enriched using ClueGO+CluePedia Plug-in. Results: GAPDH, PRDM10, TP53, AKT1, INS, ALB, SRC, MAPK1, ACLY, ACACA, DECR1, ACACB, MBOAT4, TNF, EHHADH and JUN genes were introduced as key genes related to the fat diet fed NAFLD rats. Fatty acid biosynthesis and four other terms were introduced as the main related ones to the essential genes. Conclusion: The introduced critical genes and the related terms may describe NAFLD molecular condition and its progression to the other severe metabolic diseases. Moreover, these potential biomarkers may be monitored for diagnosis and treatment approaches after validation investigations.

Published
2017

47. Omentin-1 rs2274907 and resistin rs1862513 polymorphisms influence genetic susceptibility to nonalcoholic fatty liver disease

Author

Kohan, Leila, Safarpur, Mehrnush, and Abdollahi, Hamed

Subjects
ITLN, nutritional and metabolic diseases, Original Article, Resistin, Polymorphism, digestive system diseases, Non-alcoholic fatty liver disease
Abstract

Nonalcoholic fatty liver disease (NAFLD) is an obesity-associated disease and dysregulation of adipokines has an important role in its development. Omentin-1 (ITLN1 protein) and resistin are two adipokine secreted from adipose tissue. Single nucleotide polymorphisms in the adipokine genes may affect expression and activity of the adipokine, and thus play a contributory role in NAFLD pathogenesis. The aim of the present study was to investigate the association between omentin-1 rs2274907 (326A/T) and resistin rs1862513 (-420 C/G) polymorphisms and risk of NAFLD in Iranian patients. This case-control study was done on 282 subjects included 94 patients with NAFLD and 188 healthy peoples. The genotypes were determined using PCR-RFLP method. The frequency of omentin-1 AT genotype in patients with NAFLD was significantly different from that in the control (OR=2.3, 95% CI: 1.3-3.8, P=0.003). A significant association was observed between NAFLD and the GG genotype regarding resistin rs1862513 polymorphism (OR=2.3, 95% CI: 1.1-4.8, P=0.03). In conclusion, Omentin-1 rs2274907 and resistin rs1862513 polymorphisms might be a candidate genetic factor for susceptibility to NAFLD.

Published
2016

48. The Effects of Hesperidin on BDNF/TrkB Signaling Pathway and Oxidative Stress Parameters in the Cerebral Cortex of the Utero-placental Insufficiency Fetal Rat Model.

Author

Abdollahi, Hamed, Edalatmanesh, Mohammad Amin, Hosseini, Ebrahim, and Foroozanfar, Mohsen

Subjects
*ANIMAL disease models, *CELLULAR signal transduction, *CEREBRAL cortex, *OXIDATIVE stress, *BRAIN-derived neurotrophic factor
Abstract

Introduction: Uteroplacental Insufficiency (UPI) produces critical neurodevelopmental problems affecting the Intrauterine Growth Restricted (IUGR) in offspring. This study aimed to investigate the possible neuroprotective roles of Hesperidin (Hes) on the fetal cerebral cortex of the UPI rat model. Methods: In this experimental study, 40 pregnant Wistar rats (age: ~40 days, Mean±SD weight: 180±10 g) were randomly divided into 5 groups (n= 8/group). The study groups included control (normal saline, orally), UPI+NS (uterine vessel ligation+normal saline, orally), UPI+HES25, UPI+HES50, and UPI+HES100 (uterine vessel ligation+25, 50 and 100 mg/kg Hes, orally). After being anesthetized by ketamine and xylazine, UPI was induced by permanent bilateral closure of the uterine vessels on Gestation Day (GD) 18. From GD15, the Hes/NS-treated groups received Hes/normal saline until GD21. On GD21, the uterus, placenta, and fetus were dissected out and weighed. The oxidative stress parameters, including Catalase (CAT) activity, Malondialdehyde (MDA), and Total Antioxidant Capacity (TAC) were measured in the fetal cerebral cortex. The expression of Brain-Derived Neurotrophic Factor (BDNF) and Tropomyosin Receptor Kinase B (TrkB) was assessed by RT qPCR methods. The obtained data were analyzed by Analysis of Variance (ANOVA) and Tukey's post hoc test. Results: The present study findings identified a significant difference in the uterine and fetus weight in Hes-treated mothers (P< 0.05). In the fetus, Hes reduced MDA, and increased CAT activity and TAC (P=0.001 in the UPI+Hes100 group, compared to the UPI+NS group). UPI reduced BDNF and TrkB mRNA expression, compared to the control group (P<0.05). Also, Significant increases in BDNF and TrkB mRNA expression were observed after administrating Hes in the fetal cerebral cortex of the UPI rat model, in a dose-dependent manner (P<0.05). Conclusion: Hes, as a neuroprotective and antioxidant agent, accelerates BDNF-TrkB signaling pathway and suppresses oxidative stress parameters in the cerebral cortex of the UPI rat model. [ABSTRACT FROM AUTHOR]

Published
2021
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50. The Biochemical Parameters and Vitamin D Levels in ICU Patients withCovid-19: A Cross-Sectional Study

Author

Abdollahi, Hamed, Salehinia, Farahnaz, Badeli, Mostafa, Karimi, Elmira, Gandomkar, Hossein, Asadollahi, Amin, Sedighiyan, Mohsen, and Abdolahi, Mina

Abstract

Background: In Covid-19 infection, leukopenia, inflammation, and elevated liver enzymesare found in most patients. Also, vitamin D deficiency attenuates the immune system andpredisposes a person to being more susceptible to infection. In this context, we aimed to evaluate vitaminD, electrolytes, complete blood count, liver enzymes, urea, creatinine, albumin, CRP andESR levels in patients with Covid-19. Methods: We conducted a cross-sectional study on 118 patients with Covid-19 who were hospitalizedfrom 2020/2/19 to 2020/4/3 in ICU. Serum levels of electrolytes, liver enzymes, blood factors,urea, creatinine, CRP and ESR, as well as anthropometric parameters and serum vitamin D concentration,were measured. Results: A total of 118 patients (80 male and 38 female) were enrolled in the study (65.05±15.75years). Only 5.08% of patients had no risk factors and 55.9% had ≥ 2 risk factors. Diabetes(44.1%) and obesity (23.7%) were more common among patients. Laboratory findings showed that80.50% of patients had hyponatremia, but other electrolytes including K, Mg, Ca and P were normalin the majority of participants as well as CBC, Cr, Urea, Alb, ALT and ALKP. The AST concentrationincreased in most patients (66.94%). All patients had high levels of inflammatory factorssuch as CRP and ESR. The mean of 25-hydroxy-vitamin D levels in participants (25.95 ± 14.56ng/mL) was lower than its levels in the general population. However, it was not statistically significant(P= 0.88). A significant negative correlation was found between vitamin D and ALT (P= 0.02,-0.21) as well as vitamin D and CRP (P= 0.05, -0.17). Conclusion: Due to the regulatory role of vitamin D in the immune system and low levels of vitaminD in Covid-19 infected patients, the evaluation of vitamin D levels and prescribed supplements,if necessary, is suggested.

Published
2021
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