Latest AI and machine learning research in work force for healthcare professionals.
The diversity of training datasets is usually perceived as an important aspect to obtain a robust mo...
Explainable Artificial Intelligence (XAI) is increasingly essential as AI systems are deployed in cr...
Background and Objective: Increasing screening volumes, combined with global shortage of radiologist...
Video quality significantly affects video classification. We found this problem when we classified M...
Vision-language models (VLMs) face significant computational inefficiencies caused by excessive gene...
Malawi's HIV treatment monitoring system faces serious challenges because of a shortage of experts a...
Vision-language models (VLMs) face significant computational inefficiencies caused by excessive gene...
Utility companies increasingly rely on drone imagery for post-event and routine inspection, but trai...
In order to navigate complex traffic environments, self-driving vehicles must recognize many semanti...
Background: The 2024 blood culture bottle shortage brought diagnostic resource allocation to the for...
In previous work, we achieved state-of-the-art performance on ChestX-ray14 (ROC-AUC 0.940, F1 0.821)...
While protein language models (PLMs) have shown great promise for protein design, their performance ...
Echocardiography is critical for diagnosing cardiovascular diseases, yet the shortage of skilled son...
Large Vision-Language Models (LVLMs) have adopted visual token pruning strategies to mitigate substa...
Background: Systematic reviews are important for informing public health policies and program select...
Colonoscopy video generation delivers dynamic, information-rich data critical for diagnosing intesti...
In recent times, large datasets hinder efficient model training while also containing redundant conc...
Background: Objective Structured Clinical Examination (OSCE; Clinical Performance Examination [CPX] ...
Text-to-image (T2I) models are rapidly gaining popularity, yet their outputs often lack geographical...
Large Language Models (LLMs) are converging towards a singular Artificial Hivemind, where shared Nat...
Background: Diagnostic errors are a leading cause of preventable patient harm, often occurring durin...