Artificial Intelligence Medical Compendium

Background: Rheumatic mitral stenosis (RMS) disproportionately affects low-resource settings where echocardiography is limited. We evaluated foundation model (FM) feasibility for RMS detection using limited, indirectly labeled ECGs. Methods: An ECG-F... read more 

Multimodal large language models have advanced rapidly, but most remain optimized for single-image inputs. Multi-image reasoning is costly because each image adds many visual tokens, increasing encoding and attention demands. Existing techniques that... read more 

In robot-assisted partial nephrectomy (RAPN), experts and novices differ in many metrics, but it is unknown which difference relates to novice operative efficiency and whether it improves with early experience. We addressed these questions using rout... read more 

The accuracy of machine learning interatomic potentials suffers from reference data that contain numerical noise. Often originating from unconverged or inconsistent electronic-structure calculations, this noise is challenging to identify. Existing mi... read more 

PURPOSE: Ambient artificial intelligence (AI) scribes aim to reduce documentation burden, yet evidence in urology is limited. We evaluated the pilot rollout of an AI scribe system in our academic urology department, focusing on user experience and el... read more 

Molecular imaging technologies have transformed analytical chemistry by enabling molecular identification and spatial localization within intact biological specimens. Advances in mass spectrometry imaging (MSI), Raman imaging, imaging mass cytometry ... read more 

Following the advent of generative artificial intelligence (GenAI), seeking health information on GenAI has become a more common and flexible approach. However, laypeople's health information seeking and processing (HISP) motivations and behavior on ... read more 

PURPOSE: To evaluate the efficacy of a computed tomography pulmonary angiography (CTPA)-based artificial intelligence system for use in the clinical setting to stratify the risk of pulmonary embolism (PE). MATERIALS AND METHODS: This study enrolled 1... read more 

OBJECTIVE: Using a machine learning model, the authors aimed to predict self-harm events within 90 days of an emergency department (ED) visit associated with a mental or substance use disorder diagnosis. METHODS: Electronic health record and claims d... read more 

To date the environmental impacts of production of most chemicals are unknown, hindering sustainable process evaluation and design. Life cycle assessment (LCA) is the most comprehensive method for estimating these environmental impacts but existing L... read more