Machine Learning Models Highlight the Impact of Pollution and Weather Patterns on Relapse Occurrence in Multiple Sclerosis Patients

Authors: Marinello, Elena, Tavazzi, Erica, Longato, Enrico, Bosoni, Pietro, Dagliati, Arianna, Vazifehdan, Mahin, Bellazzi, Riccardo, Trescato, Isotta, Guazzo, Alessandro, Vettoretti, Martina, Tavazzi, Eleonora, Ahmad, Lara, Bergamaschi, Roberto, Cavalla, Paola, Manera, Umberto, Chio, Adriano, Di Camillo, Barbara

Source: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) Bioinformatics and Biomedicine (BIBM), 2024 IEEE International Conference on. :6161-6168 Dec, 2024

Relation: 2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Utilizing Gyroscope and Accelerometer for Self-Managed Crystal Methamphetamine Recovery and Private Monitoring

Authors: Ahmed, Ali, Amr, Omar, Atia, Ayman

Source: 2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC) Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), 2024 International. :1-6 Nov, 2024

Relation: 2024 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC)

Enhanced Breast Cancer Relapse Prediction using Ensemble Learning Techniques

Authors: Tripathi, Mukesh Kumar, Ananya, Meka, Murthy, V.N.L.N, Shashank, Tumma, Reddy, Jale Subash, Attaluri, Kaushal

Source: 2024 4th International Conference on Sustainable Expert Systems (ICSES) Sustainable Expert Systems (ICSES), 2024 4th International Conference on. :918-923 Oct, 2024

Relation: 2024 4th International Conference on Sustainable Expert Systems (ICSES)

A Machine Learning Approach to Analyze the Drug Addiction

Authors: Kumara, U.G.H.T, Siriwardana, S.S.A, Weerasinghe, Lokesha, Shavindi, R.A.K.I, Chiranjeewa, H.P.R.C., Siriwardana, Samanthi

Source: 2023 5th International Conference on Advancements in Computing (ICAC) Advancements in Computing (ICAC), 2023 5th International Conference on. :113-118 Dec, 2023

Relation: 2023 5th International Conference on Advancements in Computing (ICAC)

Relapse Prediction from Long-Term Wearable Data Using Self-Supervised Learning and Survival Analysis

Authors: Fekas, E., Zlatintsi, A., Filntisis, P. P., Garoufis, C., Efthymiou, N., Maragos, P.

Source: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2023 - 2023 IEEE International Conference on. :1-5 Jun, 2023

Relation: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Psychotic Relapse Prediction in Schizophrenia Patients Using A Personalized Mobile Sensing-Based Supervised Deep Learning Model

Authors: Lamichhane, B., Zhou, J., Sano, A.

Source: IEEE Journal of Biomedical and Health Informatics IEEE J. Biomed. Health Inform. Biomedical and Health Informatics, IEEE Journal of. 27(7):3246-3257 Jul, 2023

Towards Unsupervised Subject-Independent Speech-Based Relapse Detection in Patients with Psychosis using Variational Autoencoders

Authors: Garoufis, C., Zlatintsi, A., Filntisis, P. P., Efthymiou, N., Kalisperakis, E., Karantinos, T., Garyfalli, V., Lazaridi, M., Smyrnis, N., Maragos, P.

Source: 2022 30th European Signal Processing Conference (EUSIPCO) European Signal Processing Conference (EUSIPCO), 2022 30th. :175-179 Aug, 2022

Relation: 2022 30th European Signal Processing Conference (EUSIPCO)

The nomogram model predicts relapse risk in myelin oligodendrocyte glycoprotein antibody-associated disease: a single-center study

Authors: Jiafei Cheng, Zhuoran Wang, Jing Wang, Xiaomin Pang, Jianli Wang, Meini Zhang, Junhong Guo, Huaxing Meng

Source: Frontiers in Immunology, Vol 16 (2025)

Subject Terms: myelin oligodendrocyte glycoprotein, myelin oligodendrocyte glycoprotein antibody-associated disorder, relapse prediction, nomogram, risk factors, Immunologic diseases. Allergy, RC581-607

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fimmu.2025.1527057/full; https://doaj.org/toc/1664-3224

Access URL: https://doaj.org/article/1be0ebb0e91b428c940600b31555d8e9

Classifying the Risk of Relapse in Multiple Myeloma

Authors: Koul, Nimrita, Manvi, Sunilkumar S

Source: 2020 IEEE International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET) Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET), 2020 IEEE International Conference on. :1-4 Dec, 2020

Relation: 2020 IEEE International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET)

Computational flow cytometry immunophenotyping at diagnosis is unable to predict relapse in childhood B-cell Acute Lymphoblastic Leukemia

Authors: Martínez-Rubio, Álvaro ^{a, b, ⁎}, Chulián, Salvador ^{a, b}, Niño-López, Ana ^{a, b}, Picón-González, Rocío ^{a, b}, Rodríguez Gutiérrez, Juan F. ^c, Gálvez de la Villa, Eva ^c, Caballero Velázquez, Teresa ^d, Molinos Quintana, Águeda ^d, Castillo Robleda, Ana ^{e, f}, Ramírez Orellana, Manuel ^{e, f, g}, Martínez Sánchez, María Victoria ^{h, i}, Minguela Puras, Alfredo ^{h, i}, Fuster Soler, José Luis ^{i, j}, Blázquez Goñi, Cristina ^{b, d}, Pérez-García, Víctor M. ^k, Rosa, María ^{a, b}

Source: In Computers in Biology and Medicine April 2025 188

Opioid Relapse Prediction with GAN

Authors: Yang, Zhou, Nguyen, Long H., Jin, Fang

Source: 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Advances in Social Networks Analysis and Mining (ASONAM), 2019 IEEE/ACM International Conference on. :560-567 Aug, 2019

Relation: 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A comprehensive review

Authors: Yasin, Sana ^{a, b, ∗}, Othmani, Alice ^c, Raza, Imran ^a, Hussain, Syed Asad ^a

Source: In Computers in Biology and Medicine June 2023 159

Editorial: Addiction and the brain: current knowledge, methods, and perspectives

Authors: Hao Chen, Sören Kuitunen-Paul, Aviv M. Weinstein, Johannes Petzold

Source: Frontiers in Psychiatry, Vol 14 (2023)

Subject Terms: addiction, substance use disorder (SUD), non-invasive brain stimulation, relapse prediction, addiction treatment, behavioral addictions, Psychiatry, RC435-571

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fpsyt.2023.1343524/full; https://doaj.org/toc/1664-0640

Access URL: https://doaj.org/article/dc101aeda470499c8dceb511f41053d9

Early relapse prediction after allogeneic hematopoietic stem cell transplantation for acute lymphoblastic leukemia (ALL) using lineage‐specific chimerism analysis

Authors: Hannes Lindahl, Davide Valentini, Sofie Vonlanthen, Mikael Sundin, Andreas T. Björklund, Stephan Mielke, Dan Hauzenberger

Source: eJHaem, Vol 3, Iss 4, Pp 1277-1286 (2022)

Subject Terms: acute leukemia, chimerism analysis, relapse prediction, stem cell transplantation, Diseases of the blood and blood-forming organs, RC633-647.5

File Description: electronic resource

Relation: https://doaj.org/toc/2688-6146

Access URL: https://doaj.org/article/50c91d7be6d64a1aa65db8d130e743de

A Wegner's Granulomatosis Risk Prediction Model Based on Machine Learning Algorithms

Authors: Jaleh Shoshtarian Malak, Samira Alesaeidi, Fatemeh Haji Ali Asgari, Fahimeh Khedmatkon

Source: Journal of Biostatistics and Epidemiology, Vol 9, Iss 2 (2023)

Subject Terms: Wegener's granulomatosis relapse, Relapse prediction, Machine learning, Clinical decision-making, Xgboost algorithm, Birmingham vasculitis activity score, Biology (General), QH301-705.5, Probabilities. Mathematical statistics, QA273-280

File Description: electronic resource

Relation: https://jbe.tums.ac.ir/index.php/jbe/article/view/942; https://doaj.org/toc/2383-4196; https://doaj.org/toc/2383-420X

Access URL: https://doaj.org/article/ec9bb10686f34305b741e23eff7c47ad

Early assessment of circulating tumor DNA after curative‐intent resection predicts tumor recurrence in early‐stage and locally advanced non‐small‐cell lung cancer

Authors: Silvia Waldeck, Jan Mitschke, Sebastian Wiesemann, Michael Rassner, Geoffroy Andrieux, Max Deuter, Jurik Mutter, Anne‐Marie Lüchtenborg, Daniel Kottmann, Laurin Titze, Christoph Zeisel, Martina Jolic, Ulrike Philipp, Silke Lassmann, Peter Bronsert, Christine Greil, Justyna Rawluk, Heiko Becker, Lisa Isbell, Alexandra Müller, Soroush Doostkam, Bernward Passlick, Melanie Börries, Justus Duyster, Julius Wehrle, Florian Scherer, Nikolas von Bubnoff

Source: Molecular Oncology, Vol 16, Iss 2, Pp 527-537 (2022)

Subject Terms: circulating tumor DNA, early‐stage and locally advanced non‐small‐cell lung cancer, minimal residual disease, noninvasive biomarker, relapse prediction, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282

File Description: electronic resource

Relation: https://doaj.org/toc/1574-7891; https://doaj.org/toc/1878-0261

Access URL: https://doaj.org/article/4399d10b1bd049f3a353a6cfadf469f6

A multimodal computer-aided diagnostic system for depression relapse prediction using audiovisual cues: A proof of concept

Authors: Alice Othmani, Assaad Oussama Zeghina

Source: Healthcare Analytics, Vol 2, Iss , Pp 100090- (2022)

Subject Terms: Clinical depression, Clinical decision support, Deep learning, Depression relapse prediction, Biomedical video processing, Predictive analytics, Computer applications to medicine. Medical informatics, R858-859.7

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2772442522000387; https://doaj.org/toc/2772-4425

Access URL: https://doaj.org/article/be267a3923bd4e2fb98e2d9424a67f6a

Deep learning-based relapse prediction of neuromyelitis optica spectrum disorder with anti-aquaporin-4 antibody

Authors: Liang Wang, Lei Du, Qinying Li, Fang Li, Bei Wang, Yuanqi Zhao, Qiang Meng, Wenyu Li, Juyuan Pan, Junhui Xia, Shitao Wu, Jie Yang, Heng Li, Jianhua Ma, Jingzi ZhangBao, Wenjuan Huang, Xuechun Chang, Hongmei Tan, Jian Yu, Lei Zhou, Chuanzhen Lu, Min Wang, Qiang Dong, Jiahong Lu, Chongbo Zhao, Chao Quan

Source: Frontiers in Neurology, Vol 13 (2022)

Subject Terms: neuromyelitis optica spectrum disorder, anti-aquaporin-4 antibody, machine learning, deep learning, relapse prediction, Neurology. Diseases of the nervous system, RC346-429

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fneur.2022.947974/full; https://doaj.org/toc/1664-2295

Access URL: https://doaj.org/article/014b21b325b141949c5f67fc9daed6b9

Deep Learning-Based Multi-Omics Integration Robustly Predicts Relapse in Prostate Cancer

Authors: Ziwei Wei, Dunsheng Han, Cong Zhang, Shiyu Wang, Jinke Liu, Fan Chao, Zhenyu Song, Gang Chen

Source: Frontiers in Oncology, Vol 12 (2022)

Subject Terms: prostate cancer, relapse prediction, multi-omics, autoencoder, deep learning, H2O package, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fonc.2022.893424/full; https://doaj.org/toc/2234-943X

Access URL: https://doaj.org/article/acd5ee0ff33c4f0892c21f1af09701bf

Risk Factors and Nomogram for Predicting Relapse Risk in Pediatric Neuromyelitis Optica Spectrum Disorders

Authors: Shanchao Zhang, Shan Qiao, Haiyun Li, Ranran Zhang, Meiling Wang, Tao Han, Xuewu Liu, Yunshan Wang

Source: Frontiers in Immunology, Vol 13 (2022)

Subject Terms: aquaporin-4, myelin oligodendrocyte glycoprotein, neuromyelitis optica spectrum disorders, relapse prediction, pediatric patient, Immunologic diseases. Allergy, RC581-607

File Description: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fimmu.2022.765839/full; https://doaj.org/toc/1664-3224

Access URL: https://doaj.org/article/f46e26ca06c542fabfbea1d59988cc48