Explainable AI machine learning framework for chronic kidney disease prediction utilizing electronic health records

Machine learning for predicting institutionalization and mortality risks among older home care recipients with routinely collected need assessment data: explainable AI for long-term care

Hongsoo Kim, Jimin Yoon, Hyerim Noh, Sunghun Yun, Seungyeon Chun, Woojoo Lee

AI-powered risk prediction models for preventable maternal mortality in rural settings: a systematic review

Joy Aifuobhokhan, Ayodeji Ogunjinmi, Chukwuemeka Abraham Agbarakwe, Deborah Oladunmolu Oduguwa, Annie Peter Essiet, Temitayo Osunkiyesi, et al.

Maternal mortality remains disproportionately high in low- and middle-income countries, particularly in rural settings with limited access to skilled obstetric care. Artificial intelligence and machine learning models offer promise for early risk prediction, yet their methodologi…Read more

Development and temporal validation of a machine learning-based model for predicting renal impairment in multiple myeloma: a single-center retrospective cohort study

Manli Zhou, Sisi Feng

Multiple myeloma (MM) is a hematopoietic system malignancy characterized by clonal proliferation of abnormal plasma cells, commonly presenting with renal impairment (RI) that significantly impacts patient’s quality of life. The objective of this study was to develop a predictive…Read more

Correction: Diagnostic performance of machine learning and deep learning algorithms for thyroid cancer metastasis: a systematic review and meta-analysis

Mohammad Amouzadeh Lichahi, Saeid Anvari, Hossein Hemmati, Ervin Zadgari, Maryam Jafari, Seyedeh Mohadeseh Mosavi Mirkalaie, et al.

Multitask learning of longitudinal circulating biomarkers and clinical outcomes: identification of optimal machine-learning and deep-learning models

Min Yuan, Shixin Su, Haolun Ding, Yaning Yang, Manish Gupta, Xu Steven Xu

AI-powered spectral CT analysis for clinical decision support in carotid vulnerable plaque detection: a deep learning approach

Yunzhe Ni, Tianyu Zhang, Zonghui Huang, Yue Wang, Guochao Han, Lin Yuan, et al.

Carotid vulnerable plaques (CVPs) represent a major cause of ischemic stroke, yet current diagnostic methods lack sufficient precision for early detection. Spectral computed tomography (CT) enables detailed plaque characterization, but its clinical utility depends on advanced ana…Read more