Latest AI and machine learning research in work force for healthcare professionals.
Vision-language models (VLMs) face significant computational inefficiencies caused by excessive gene...
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...
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...
Background: Typing in the electronic health record (EHR) takes up healthcare providers' time and cog...
Background: EHR documentation and chart review contribute to clinician workload and burnout. To alle...
Despite high semantic alignment, modern text-to-image (T2I) generative models still struggle to synt...
Compositional generalization, the ability to reason about novel combinations of familiar concepts, i...
Sodium azide mutagenesis offers a powerful approach to generate genetic diversity for rice improveme...
Ecological theory predicts that local species richness can influence biogeographic rates of speciati...
Dataset distillation compresses the original data into compact synthetic datasets, reducing training...
Text-to-video generation is expensive, so only a few samples are typically produced per prompt. In t...