Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This study aimed to compare the performance of multiple machine learning (ML) models with the traditional Cox proportional hazards (CoxPH) model in predict...
Sepsis, a multifaceted syndrome driven by an imbalanced host response to infection, remains a significant medical challenge. At its core lies the pivotal role of glycolysis, orchestrating immune responses especially in severe sepsis. The intertwined ...
We present a survey of the current state-of-the-art in breast cancer detection and prognosis. We analyze the evolution of Artificial Intelligence-based approaches from using just uni-modal information to multi-modality for detection and how such para...
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Sep 26, 2024
BACKGROUND: Advancements in machine learning (ML) have improved the accuracy of models that predict human immunodeficiency virus (HIV) incidence. These models have used electronic medical records and registries. We aim to broaden the application of t...
BACKGROUND: Schizophrenia is a complex and disabling mental disorder that represents one of the most important challenges for neuroimaging research. There were many attempts to understand these basic mechanisms behind the disorder, yet we know very l...
Studies in health technology and informatics
Sep 24, 2024
Reoperation is the most significant complication following any surgical procedure. Developing machine learning methods that predict the need for reoperation will allow for improved shared surgical decision making and patient-specific and preoperative...
Studies in health technology and informatics
Sep 24, 2024
Depression significantly impacts the wellbeing of older Australians, posing considerable challenges to their overall quality of life. This study aimed to detect in-home movement patterns of participants that could be indicative of depressive states. ...
Ischemic stroke (IS) is a leading cause of adult disability that can severely compromise the quality of life for patients. Accurately predicting the IS functional outcome is crucial for precise risk stratification and effective therapeutic interventi...
We sought to develop and validate a machine learning (ML) model for predicting multidimensional frailty based on clinical and laboratory data. Moreover, an explainable ML model utilizing SHapley Additive exPlanations (SHAP) was constructed. This stud...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.