PURPOSE: To determine the accuracy of large language models (LLMs) in generating appropriate treatment options for patients with early breast cancer on the basis of their medical records.
BACKGROUND: Medication adherence plays a crucial role in determining the health outcomes of patients, particularly those with chronic conditions like type 2 diabetes. Despite its significance, there is limited evidence regarding the use of machine le...
The rupture of vulnerable plaques is the principal cause of luminal thrombosis in acute ischemic stroke. The identification of plaque features that indicate risk for disruption may predict cerebrovascular events. Here, we aimed to build a high-risk i...
Concerns about the generalizability of machine learning models in mental health arise, partly due to sampling effects and data disparities between research cohorts and real-world populations. We aimed to investigate whether a machine learning model t...
Clinical chemistry and laboratory medicine
Mar 19, 2025
OBJECTIVES: Human tear analysis holds promise for biomarker discovery, but its clinical utility is hindered by the lack of standardized reference values, limiting interindividual comparisons. This study aimed at developing a protocol for normalizing ...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Mar 19, 2025
BACKGROUND: In the HECKTOR 2022 challenge set [1], several state-of-the-art (SOTA, achieving best performance) deep learning models were introduced for predicting recurrence-free period (RFP) in head and neck cancer patients using PET and CT images.
OBJECTIVE: Prostate cancer (PCa) is highly heterogeneous, making early detection of adverse pathological features crucial for improving patient outcomes. This study aims to predict PCa aggressiveness and identify radiomic and protein biomarkers assoc...
BACKGROUND: Heart failure (HF) is a complex syndrome with varied presentations and progression patterns. Traditional classification systems based on left ventricular ejection fraction (LVEF) have limitations in capturing the heterogeneity of HF. We a...
Stroke is a leading cause of death and disability in developed countries. We validated an AI-based prediction model for incident stroke using sensors such as fundus cameras and ophthalmoscopes for retinal images, along with socio-demographic data and...
BACKGROUND: World Health Organization (WHO) identified noncommunicable diseases as the foremost risk to public health globally and the cause of approximately 80% of premature deaths. However, Cardiovascular diseases account for most of these prematur...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.