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2. Predictive Deep Learning: An Analysis of Inception V3, VGG16, and VGG19 Models for Breast Cancer Detection

Author

Kansal, Kanika, Sharma, Sanjiv, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Garg, Deepak, editor, Rodrigues, Joel J. P. C., editor, Gupta, Suneet Kumar, editor, Cheng, Xiaochun, editor, Sarao, Pushpender, editor, and Patel, Govind Singh, editor

Published
2024
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3. A Novel Bagged Ensemble Approach for Accurate Histopathological Breast Cancer Classification Using Transfer Learning and Convolutional Neural Networks

Author

Nakach, Fatima-Zahrae, Idri, Ali, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Rocha, Ana Paula, editor, Steels, Luc, editor, and van den Herik, Jaap, editor

Published
2024
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4. Breast Cancer Radiogenomics Data Generation Using Combined Generative Adversarial Networks GANs

Author

Anwar, Suzan, Ali, Shereen, Abdulla, Dalya, Omekara, Sam Davis, Mendiola, Salavador, Wright, Kai, Muhammed, Saja Ataallah, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bennour, Akram, editor, Bouridane, Ahmed, editor, and Chaari, Lotfi, editor

Published
2024
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5. Simulation-Based Treatment Protocol Design for Damaging Breast Tumor Using Laser Photothermal Therapy

Author

Quinn, Edwin, Singh, Manpreet, Zhu, Liang, Tavares, João Manuel R. S., Series Editor, Jorge, Renato Natal, Series Editor, Cohen, Laurent, Editorial Board Member, Doblare, Manuel, Editorial Board Member, Frangi, Alejandro, Editorial Board Member, Garcia-Aznar, Jose Manuel, Editorial Board Member, Holzapfel, Gerhard A., Editorial Board Member, Hughes, Thomas J.R., Editorial Board Member, Kamm, Roger, Editorial Board Member, Li, Shuo, Editorial Board Member, Löhner, Rainald, Editorial Board Member, Nithiarasu, Perumal, Editorial Board Member, Oñate, Eugenio, Editorial Board Member, Perales, Francisco J., Editorial Board Member, Prendergast, Patrick J., Editorial Board Member, Tamma, Kumar K., Editorial Board Member, Vilas-Boas, Joao Paulo, Editorial Board Member, Weiss, Jeffrey, Editorial Board Member, Zhang, Yongjie Jessica, Editorial Board Member, Skalli, Wafa, editor, Laporte, Sébastien, editor, and Benoit, Aurélie, editor

Published
2024
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6. Prediction of Breast Cancer Using Machine Learning Technique

Author

Namdev, Madhav P., Ansari, Sakil Ahmad, Singh, Arjun, Choudhary, Pushpa, Singh, Arun Kumar, Kumar, Jaideep, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Garg, Deepak, editor, Rodrigues, Joel J. P. C., editor, Gupta, Suneet Kumar, editor, Cheng, Xiaochun, editor, Sarao, Pushpender, editor, and Patel, Govind Singh, editor

Published
2024
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7. A Predictive Deep Learning Ensemble-Based Approach for Advanced Cancer Classification

Author

Kansal, Kanika, Sharma, Sanjiv, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Garg, Deepak, editor, Rodrigues, Joel J. P. C., editor, Gupta, Suneet Kumar, editor, Cheng, Xiaochun, editor, Sarao, Pushpender, editor, and Patel, Govind Singh, editor

Published
2024
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10. Correctness and Completeness of Breast Cancer Diagnoses Recorded in UK CPRD Aurum and CPRD GOLD Databases: Comparison to Hospital Episode Statistics and Cancer Registry (Companion Paper 2)

Author

Hagberg KW, Vasilakis-Scaramozza C, Persson R, Neasham D, Kafatos G, and Jick S

Subjects
cprd aurum, cprd gold, breast cancer, validation, Infectious and parasitic diseases, RC109-216
Abstract

Katrina Wilcox Hagberg,1 Catherine Vasilakis-Scaramozza,2 Rebecca Persson,1 David Neasham,2 George Kafatos,2 Susan Jick1,3 1Epidemiology, Boston Collaborative Drug Surveillance Program, Lexington, MA, USA; 2Center for Observational Research, Amgen Ltd, Uxbridge, UK; 3Epidemiology, Boston University School of Public Health, Boston, MA, USACorrespondence: Susan Jick, Boston Collaborative Drug Surveillance Program, 11 Muzzey Street, Lexington, MA, 02421, USA, Tel +1 781 862 6660, Fax +1 781 862 1680, Email sjick@bu.eduPurpose: To evaluate the new Clinical Practice Research Datalink (CPRD) Aurum database, we estimated ‘correctness’ (ie accuracy, validity) and ‘completeness’ (ie presence, missingness) of malignant breast cancer diagnoses recorded in CPRD Aurum compared to external linked data sources: Hospital Episode Statistics (HES) Admitted Patient Care (APC), HES Outpatient (OP), and Cancer Registry (CR), and to the previously validated CPRD GOLD.Methods: Linkage-eligible, female patients with incident malignant breast cancer diagnosis recorded in at least one study data source were selected. Correctness was the proportion of malignant breast cancer cases recorded in CPRD Aurum or GOLD who also had a diagnosis recorded in HES APC/OP (2004– 2019) or CR (2004– 2016). Completeness was estimated by identifying all malignant breast cancer diagnoses in HES APC/OP or CR and calculating the proportion with a concordant diagnosis in CPRD Aurum or GOLD.Results: Compared to HES APC/OP, there were 85,659 and 31,452 eligible patients in CPRD Aurum and GOLD, respectively. Correctness estimates were high (CPRD Aurum 83.5%, GOLD 81.7%). Compared to CR, there were 70,190 and 29,597 eligible patients in CPRD Aurum and GOLD, respectively: correctness was 89.1% for CPRD Aurum and 88.2% for GOLD. Completeness estimates for CPRD Aurum and GOLD were high (> 90%). Diagnoses were recorded in CPRD Aurum within − 7 to 74 days of those in the linked sources. Reasons for discordant diagnostic coding included presence of treatment or other clinical codes only, diagnosis coded after end of follow-up, non-malignant breast cancer in linked data, and administrative codes in lieu of diagnostic codes.Conclusion: These results indicate that correctness and completeness of malignant breast cancer diagnoses in CPRD Aurum were high and similar to CPRD GOLD. This provides confidence in use of CPRD Aurum for research purposes. Where complete case capture is important, researchers should consider linkage to HES APC or CR.Keywords: CPRD Aurum, CPRD GOLD, breast cancer, validation

Published
2023

11. Presence of Breast Cancer Information Recorded in United Kingdom Primary Care Databases: Comparison of CPRD Aurum and CPRD GOLD (Companion Paper 1)

Author

Hagberg KW, Vasilakis-Scaramozza C, Persson R, Neasham D, Kafatos G, and Jick S

Subjects
clinical practice research datalink, cprd aurum, cprd gold, breast cancer, validation, data quality, Infectious and parasitic diseases, RC109-216
Abstract

Katrina Wilcox Hagberg,1 Catherine Vasilakis-Scaramozza,2 Rebecca Persson,1 David Neasham,2 George Kafatos,2 Susan Jick1,3 1Epidemiology, Boston Collaborative Drug Surveillance Program, Lexington, MA, USA; 2Center for Observational Research, Amgen Ltd, Uxbridge, UK; 3Epidemiology, Boston University School of Public Health, Boston, MA, USACorrespondence: Susan Jick, Boston Collaborative Drug Surveillance Program, 11 Muzzey Street, Lexington, MA, 02421, USA, Tel +1 781 862 6660, Fax +1 781 862 1680, Email sjick@bu.eduPurpose: To evaluate the presence of data elements related to diagnosis and treatment of malignant breast cancer in CPRD Aurum compared to those in the previously validated CPRD GOLD.Methods: Females in CPRD Aurum or GOLD with a first-time code for malignant breast cancer, mastectomy, or ≥ 1 prescription for tamoxifen or aromatase inhibitors (2004– 2019) were selected. We compared the presence of the codes for breast cancer diagnosis, surgeries (mastectomy, lumpectomy), tamoxifen and aromatase inhibitor prescriptions, radiation, chemotherapy, and supporting clinical codes (suspected breast cancer, lump symptoms, biopsy, lumpectomy, cancer care, referral/visit to specialist, palliative care). Age standardized incidence rates of breast cancer diagnosis in CPRD Aurum and GOLD were calculated.Results: There were 131,936 eligible patients in CPRD Aurum and 69,102 patients in GOLD. A similar proportion of patients in CPRD Aurum and GOLD had codes for breast cancer diagnosis, mastectomy, drug prescriptions, lump, biopsy, lumpectomy, chemotherapy, and cancer and palliative care coded in their electronic record during follow-up. However, suspected breast cancer, radiation, and referral/visits to specialists were coded more frequently in patients in CPRD Aurum compared to GOLD. Age-standardized incidence rates were similar for CPRD Aurum and GOLD.Conclusion: Overall, there was consistency between data elements related to malignant breast cancer recorded in CPRD Aurum and GOLD, particularly for the most informative clinical details. These findings provide reassurance that breast cancer information recorded in CPRD Aurum is generally comparable to that recorded in the previously validated CPRD GOLD and support the use of CPRD Aurum for breast cancer research.Keywords: clinical practice research datalink, CPRD Aurum, CPRD GOLD, breast cancer, validation, data quality

Published
2023

12. Risk Stratification of Breast Cancer Patients: Integrating Epidemiology, Risk Factors, and Prognostic Markers for Sustainable Development

Author

Tripathi, Rajan Prasad, Khatri, Sunil Kumar, Van Greunen, Darelle, Ather, Danish, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Whig, Pawan, editor, Silva, Nuno, editor, Elngar, Ahmed A., editor, Aneja, Nagender, editor, and Sharma, Pavika, editor

Published
2023
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13. Mammogram Based Breast Cancer Detection with Transfer Learning

Author

Wangdi, Pema, Kumar, Dinesh, Kag, Hitesh, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Garg, Deepak, editor, Narayana, V. A., editor, Suganthan, P. N., editor, Anguera, Jaume, editor, Koppula, Vijaya Kumar, editor, and Gupta, Suneet Kumar, editor

Published
2023
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14. A Deep Learning Model for Breast Cancer Diagnosis Using Mammography Images Classification

Author

Laaffat, Nourane, Outfarouin, Ahmad, Bouarifi, Walid, Jraifi, Abdelilah, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, García Márquez, Fausto Pedro, editor, Jamil, Akhtar, editor, Eken, Süleyman, editor, and Hameed, Alaa Ali, editor

Published
2023
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15. Breast Cancer Detection by Using Decision Tree

Author

Vashist, Apurva, Sagar, Anil Kumar, Goyal, Anjali, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Shaw, Rabindra Nath, editor, Paprzycki, Marcin, editor, and Ghosh, Ankush, editor

Published
2023
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16. Comparative Assessment of Deep End-To-End, Deep Hybrid and Deep Ensemble Learning Architectures for Breast Cancer Histological Classification

Author

Zerouaoui, Hasnae, Idri, Ali, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Coenen, Frans, editor, Fred, Ana, editor, Aveiro, David, editor, Dietz, Jan, editor, Bernardino, Jorge, editor, and Masciari, Elio, editor

Published
2023
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17. False Positive Reduction in Mammographic Mass Detection

Author

Shrinithi, S., Lavanya, R., Vijayan, Devi, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Stettner, Lukasz, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Rettberg, Achim, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Fernando, Xavier, editor, and Chandrabose, Aravindan, editor

Published
2023
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18. Use of Machine Learning Models for Analyzing the Accuracy of Predicting the Cancerous Diseases

Author

Makka, Shanthi, Arora, Gagandeep, Reddy, Sai Sindhu Theja, Lingam, Sunitha, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Bhattacharya, Abhishek, editor, Dutta, Soumi, editor, Dutta, Paramartha, editor, and Piuri, Vincenzo, editor

Published
2023
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19. Enhanced and Effective Ensemble Model for Breast Cancer Detection and Prediction in Modern Medical System in Machine Learning

Author

Saravanan, T. R., Mahariba, A. Jackulin, Priya, S., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Kottursamy, Kottilingam, editor, Bashir, Ali Kashif, editor, Kose, Utku, editor, and Uthra, Annie, editor

Published
2023
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20. Robust Method for Breast Cancer Classification Based on Feature Selection Using RGWO Algorithm

Author

Mezaghrani, Ali, Debakla, Mohamed, Djemal, Khalifa, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Salem, Mohammed, editor, Merelo, Juan Julián, editor, Siarry, Patrick, editor, Bachir Bouiadjra, Rochdi, editor, Debakla, Mohamed, editor, and Debbat, Fatima, editor

Published
2023
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21. Inferring Pathological Metabolic Patterns in Breast Cancer Tissue from Genome-Scale Models

Author

Amaradio, Matteo N., Jansen, Giorgio, Ojha, Varun, Costanza, Jole, Di Fatta, Giuseppe, Nicosia, Giuseppe, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nicosia, Giuseppe, editor, Ojha, Varun, editor, La Malfa, Emanuele, editor, La Malfa, Gabriele, editor, Pardalos, Panos, editor, Di Fatta, Giuseppe, editor, Giuffrida, Giovanni, editor, and Umeton, Renato, editor

Published
2023
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23. Provision of follow-up care for women with a history of breast cancer following the 2016 position paper by the Italian Group for Mammographic Screening and the Italian College of Breast Radiologists by SIRM: a survey of Senonetwork Italian breast centres

Author

Deandrea, Silvia, Sardanelli, Francesco, Calabrese, Massimo, Ferré, Francesca, Vainieri, Milena, Sestini, Elisabetta, Caumo, Francesca, Saguatti, Gianni, Bucchi, Lauro, and Cataliotti, Luigi

Published
2022
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24. Implementation of a Method Using Image Sequentialization, Patch Embedding and ViT Encoder to Detect the Breast Cancer on RGBA Images and Binary Masks

Author

Dixit, Tanishka, Singh, Namrata, Srivastava, Geetika, Srivastava, Meenakshi, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Dev, Amita, editor, Agrawal, S. S., editor, and Sharma, Arun, editor

Published
2022
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29. Analysis of the Generation of a Synthetic Response to the Application of Contrast Agents in Breast Medical Images Using Generative Adversarial Networks

Author

Rincón, Jaider Stiven, Mera, Carlos, Fonnegra, Rubén, Díaz, Gloria M., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Narváez, Fabián R., editor, Proaño, Julio, editor, Morillo, Paulina, editor, Vallejo, Diego, editor, González Montoya, Daniel, editor, and Díaz, Gloria M., editor

Published
2022
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30. A Machine Learning-Based Congenital Categorization Approach in Early Recognition of Breast Carcinoma

Author

Singh, Sandeep, Aalam, Zunaid, Kaur, Amritpal, Manocha, Prabhjot Singh, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Nagar, Atulya K., editor, Jat, Dharm Singh, editor, Marín-Raventós, Gabriela, editor, and Mishra, Durgesh Kumar, editor

Published
2022
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31. Independent Scientific Paper by Doctors Using IceCure's ProSense Published in Journal of Breast Imaging Presents Advantages of Cryoablation Breast Conserving Over Surgery in Early Breast Cancer Patients

Subjects
Lumpectomy, Physicians, Breast cancer
Abstract

Paper cites IceCure's ICE3 interim clinical study results as evidence of safety and efficacy of cryoablation in early-stage breast cancer CAESAREA, Israel, Oct. 25, 2023 /PRNewswire/ -- https://icecure-medical.com/(Nasdaq: ICCM) ('IceCure' [...]

Published
2023

32. Detection of Breast Cancer from Mammogram Images Using Deep Transfer Learning

Author

Das, Akalpita, Das, Himanish Shekhar, Barman, Utpal, Choudhury, Arijeet, Mazumdar, Sourav, Neog, Anupal, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Thampi, Sabu M., editor, Krishnan, Sri, editor, Hegde, Rajesh M., editor, Ciuonzo, Domenico, editor, Hanne, Thomas, editor, and Kannan R., Jagadeesh, editor

Published
2021
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33. Cytological Images Clustering

Author

Berezsky, Oleh, Pitsun, Oleh, Dubchak, Lesia, Berezka, Kateryna, Dolynyuk, Taras, Derish, Bohdan, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Shakhovska, Natalya, editor, and Medykovskyy, Mykola O., editor

Published
2021
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36. Breast Cancer Classification Using Convolution Neural Network (CNN)

Author

Yadav, Rohit, Pande, Sagar, Khamparia, Aditya, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Luhach, Ashish Kumar, editor, Jat, Dharm Singh, editor, Bin Ghazali, Kamarul Hawari, editor, Gao, Xiao-Zhi, editor, and Lingras, Pawan, editor

Published
2021
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38. Machine Learning in Healthcare: Breast Cancer and Diabetes Cases

Author

Cheddad, Abbas, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Reis, Thoralf, editor, Bornschlegl, Marco X., editor, Angelini, Marco, editor, and Hemmje, Matthias L., editor

Published
2021
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39. Tackling Insomnia Symptoms through Vestibular Stimulation in Patients with Breast Cancer: A Perspective Paper

Author

Joy Perrier, Melvin Galin, Pierre Denise, Bénédicte Giffard, and Gaëlle Quarck

Subjects
sleep, insomnia, breast cancer, circadian rhythms, vestibular stimulation, chemotherapy, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Insomnia symptoms are common among patients with breast cancer (BC; 20–70%) and are predictors of cancer progression and quality of life. Studies have highlighted sleep structure modifications, including increased awakenings and reduced sleep efficiency and total sleep time. Such modifications may result from circadian rhythm alterations consistently reported in this pathology and known as carcinogenic factors, including lower melatonin levels, a flattened diurnal cortisol pattern, and lower rest-activity rhythm amplitude and robustness. Cognitive behavioral therapy and physical activity are the most commonly used non-pharmacological interventions to counter insomnia difficulties in patients with BC. However, their effects on sleep structure remain unclear. Moreover, such approaches may be difficult to implement shortly after chemotherapy. Innovatively, vestibular stimulation would be particularly suited to tackling insomnia symptoms. Indeed, recent reports have shown that vestibular stimulation could resynchronize circadian rhythms and improve deep sleep in healthy volunteers. Moreover, vestibular dysfunction has been reported following chemotherapy. This perspective paper aims to support the evidence of using galvanic vestibular stimulation to resynchronize circadian rhythms and reduce insomnia symptoms in patients with BC, with beneficial effects on quality of life and, potentially, survival.

Published
2023
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40. Cluster Analysis for Breast Cancer Patterns Identification

Author

Azevedo, Beatriz Flamia, Alves, Filipe, Rocha, Ana Maria A. C., Pereira, Ana I., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Pereira, Ana I., editor, Fernandes, Florbela P., editor, Coelho, João P., editor, Teixeira, João P., editor, Pacheco, Maria F., editor, Alves, Paulo, editor, and Lopes, Rui P., editor

Published
2021
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41. Feature Selection Optimization for Breast Cancer Diagnosis

Author

Antunes, Ana Rita, Matos, Marina A., Costa, Lino A., Rocha, Ana Maria A. C., Braga, Ana Cristina, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Pereira, Ana I., editor, Fernandes, Florbela P., editor, Coelho, João P., editor, Teixeira, João P., editor, Pacheco, Maria F., editor, Alves, Paulo, editor, and Lopes, Rui P., editor

Published
2021
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43. Tackling Insomnia Symptoms through Vestibular Stimulation in Patients with Breast Cancer: A Perspective Paper.

Author

Perrier, Joy, Galin, Melvin, Denise, Pierre, Giffard, Bénédicte, and Quarck, Gaëlle

Subjects
*BREAST cancer prognosis, *CANCER chemotherapy, *CIRCADIAN rhythms, *VESTIBULAR apparatus diseases, *CANCER patients, *MELATONIN, *PHYSICAL activity, *HEALTH behavior, *QUALITY of life, *ELECTRIC stimulation, *INSOMNIA, *VESTIBULAR stimulation, *BEHAVIOR modification, *COGNITIVE therapy
Abstract

Simple Summary: Patients with breast cancer frequently complaint from insomnia difficulties that can affect quality of life and cancer progression. Such difficulties may result from rest-activity (i.e., 24 h alternation of sleep and wake) rhythm alterations consistently reported in this pathology. Currently proposed approaches to counter insomnia difficulties in patients with breast cancer have positive effects only on sleep complaints and well-being. Moreover, such approaches may be difficult to implement shortly after chemotherapy. Innovatively, vestibular stimulation would be particularly suited to tackling insomnia symptoms in patients with breast cancer. Indeed, recent reports have shown that vestibular stimulation could improve rest-activity rhythm and sleep in healthy volunteers. This perspective paper aims to support the evidence of using vestibular stimulation to improve rest-activity rhythms and reduce insomnia symptoms in patients with BC, with beneficial effects on quality of life and, potentially, survival. Insomnia symptoms are common among patients with breast cancer (BC; 20–70%) and are predictors of cancer progression and quality of life. Studies have highlighted sleep structure modifications, including increased awakenings and reduced sleep efficiency and total sleep time. Such modifications may result from circadian rhythm alterations consistently reported in this pathology and known as carcinogenic factors, including lower melatonin levels, a flattened diurnal cortisol pattern, and lower rest-activity rhythm amplitude and robustness. Cognitive behavioral therapy and physical activity are the most commonly used non-pharmacological interventions to counter insomnia difficulties in patients with BC. However, their effects on sleep structure remain unclear. Moreover, such approaches may be difficult to implement shortly after chemotherapy. Innovatively, vestibular stimulation would be particularly suited to tackling insomnia symptoms. Indeed, recent reports have shown that vestibular stimulation could resynchronize circadian rhythms and improve deep sleep in healthy volunteers. Moreover, vestibular dysfunction has been reported following chemotherapy. This perspective paper aims to support the evidence of using galvanic vestibular stimulation to resynchronize circadian rhythms and reduce insomnia symptoms in patients with BC, with beneficial effects on quality of life and, potentially, survival. [ABSTRACT FROM AUTHOR]

Published
2023
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44. Is routine axillary lymph node dissection needed to tailor systemic treatments for breast cancer patients in the era of molecular oncology? A position paper of the Italian National Association of Breast Surgeons (ANISC).

Author

Rocco, Nicola, Ghilli, Matteo, Curcio, Annalisa, Bortul, Marina, Burlizzi, Stefano, Cabula, Carlo, Cabula, Roberta, Ferrari, Alberta, Folli, Secondo, Fortunato, Lucio, Frittelli, Patrizia, Gentilini, Oreste, Grendele, Sara, Grassi, Massimo Maria, Grossi, Simona, Magnoni, Francesca, Murgo, Roberto, Palli, Dante, Rovera, Francesca, and Sanguinetti, Alessandro

Subjects
AXILLARY lymph node dissection, MOLECULAR oncology, EPIDERMAL growth factor receptors, SENTINEL lymph node biopsy, CANCER patients, BREAST cancer
Abstract

De-escalation of axillary surgery in breast cancer (BC) management began when sentinel lymph node biopsy (SLNB) replaced axillary lymph node dissection (ALND) as standard of care in patients with node-negative BC. The second step consolidated ALND omission in selected subgroups of BC patients with up to two macrometastases and recognized BC molecular and genomic implication in predicting prognosis and planning adjuvant treatment. Outcomes from the recent RxPONDER and monarchE trials have come to challenge the previous cut-off of two SLN in order to inform decisions on systemic therapies for hormone receptor-positive (HR+), human epidermal growth factor receptor type-2 (HER2) negative BC, as the criteria included a cut-off of respectively three and four SLNs. In view of the controversy that this may lift in surgical practice, the Italian National Association of Breast Surgeons (Associazione Nazionale Italiana Senologi Chirurghi, ANISC) reviewed data regarding the latest trials on this topic and proposes an implementation in clinical practice. We reviewed the available literature offering data on the pathological nodal status of cN0 breast cancer patients. The rates of pN2 status in cN0 patients ranges from 3.5 % to 16 %; pre-surgical diagnostic definition of axillary lymph node status in cN0 patients by ultrasound could be useful to inform about a possible involvement of ≥4 lymph nodes in this specific sub-groups of women. The Italian National Association of Breast Surgeons (ANISC) considers that for HR + HER2-/cN0-pN1(sn) BC patients undergoing breast conserving treatment the preoperative workup should be optimized for a more detailed assessment of the axilla and the technique of SLNB should be optimized, if considered appropriate by the surgeon, not considering routine ALND always indicated to determine treatment recommendations according to criteria of eligibility to RxPONDER and monarch-E trials. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Carcinoma Classification from Breast Histopathology Images Using a Multi Level Spatial Fusion Mechanism of Deep Convolutional Features from Differently Stain Normalized Patches

Author

Sanyal, Ritabrata, Chakrabarty, Kunal, Reddy, Gummi Deepak, Sengupta, Vinayak, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Barbosa, Simone Diniz Junqueira, Founding Editor, Singh, Pradeep Kumar, editor, Sood, Sanjay, editor, Kumar, Yugal, editor, Paprzycki, Marcin, editor, Pljonkin, Anton, editor, and Hong, Wei-Chiang, editor

Published
2020
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46. A Novel Approach for False Positive Reduction in Breast Cancer Detection

Author

Shingan, Mayuresh, Pawar, Meenakshi, Talbar, S., Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Nain, Neeta, editor, Vipparthi, Santosh Kumar, editor, and Raman, Balasubramanian, editor

Published
2020
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47. DeepRNNetSeg: Deep Residual Neural Network for Nuclei Segmentation on Breast Cancer Histopathological Images

Author

Gour, Mahesh, Jain, Sweta, Agrawal, Raghav, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Nain, Neeta, editor, Vipparthi, Santosh Kumar, editor, and Raman, Balasubramanian, editor

Published
2020
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49. Segmentation of Breast Density Using K-Means Clustering Algorithm

Author

Dabass, Jyoti, Hanmandlu, Madasu, Vig, Rekha, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Batra, Usha, editor, Roy, Nihar Ranjan, editor, and Panda, Brajendra, editor

Published
2020
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50. Application of Data Mining and Machine Learning in Microwave Radiometry (MWR)

Author

Levshinskii, Vladislav, Galazis, Christoforos, Ovchinnikov, Lev, Vesnin, Sergey, Losev, Alexander, Goryanin, Igor, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Roque, Ana, editor, Tomczyk, Arkadiusz, editor, De Maria, Elisabetta, editor, Putze, Felix, editor, Moucek, Roman, editor, Fred, Ana, editor, and Gamboa, Hugo, editor

Published
2020
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