Clinical heterogeneity among hemodialysis patients necessitates precision medicine approaches transcending conventional single-parameter management. Through machine learning analysis of 1,207 maintenance hemodialysis patients, we developed a novel tw...
International journal of neural systems
Nov 19, 2025
This research looks at the use of long-short-term memory (LSTM) networks to predict psychosis, in patients within the schizophrenia spectrum, based on Heart Rate Variability (HRV) data acquired from wearable devices. Our primary objective is to test ...
BACKGROUND: Over 300 million individuals worldwide live with Atopic Dermatitis and Psoriasis, which are among the most common chronic inflammatory skin diseases. Multimodal biomarkers are currently being developed using large-scale data and artificia...
Carbohydrate-protein supplementation often improves endurance performance. However, effectiveness varies significantly among individuals due to unique personal characteristics. This study aimed to develop a predictive machine learning framework for p...
Postpartum diastasis recti abdominis (PDRA), characterized by pathological separation of the rectus abdominis muscles, affects 30%-60% of women, with many cases persisting beyond 6 months postpartum and having significant impacts on musculoskeletal f...
The rapid advancement of genomic and precision medicine has expanded the role of genetics and genomics in the diagnosis, risk stratification, and management of cardiovascular diseases. With the decreasing cost and increasing accessibility of genetic ...
Journal of the American Heart Association
Nov 11, 2025
BACKGROUND: Despite the established link between metabolic syndrome (MetS) and stroke incidence, the effects of dynamic and cumulative MetS scores on stroke risk among middle-aged and older populations in China remain inadequately explored. Furthermo...
BACKGROUND: Stroke remains a major global public health concern and a leading cause of death, disability, and dementia. Despite being the most important and modifiable risk factor for stroke, Blood pressure (BP) management remain controversial and ch...
Machine learning (ML) offers great potential in healthcare, especially in the analysis of complex physiological signals like electroencephalography (EEG). EEG recordings hold valuable insights into neurological function and can aid in diagnosing vari...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.