Artificial Intelligence Medical Compendium

Osteosarcoma (OS) calls for early diagnosis to significantly improve patient survival rates. Exosomes hold significant potential as noninvasive biomarkers for the early diagnosis of cancer. Here, we design a microfluidic device to purify and analyze ... read more 

A dual-mode approach was developed for dopamine (DA) assay based on boron (B) and nitrogen (N) co-doped carbon dots (B, N-CDs). This platform enabled highly sensitive and specific detection of DA in biological samples through collaborative ratio fluo... read more 

PURPOSE: The scarcity of high-quality curated labeled medical training data remains one of the major limitations in applying artificial intelligence systems to breast cancer diagnosis. Deep models for mammogram analysis and mass (or micro-calcificati... read more 

PURPOSE: We propose and evaluate multimodal deep learning (DL) approaches that combine ultrasound (US) B-mode and Nakagami parametric images for breast tumor classification. It is hypothesized that integrating tissue brightness information from B-mod... read more 

UNLABELLED: This article presents the design, implementation, and evaluation of MarIA, a GPT-3.5-powered virtual assistant integrated into a messaging platform to support patients with type 2 diabetes mellitus (DM). MarIA employs a multi-agent archit... read more 

Epilepsy is a highly prevalent chronic central nervous system disorder that imposes substantial societal and economic burdens. Inconsistent associations of alcohol consumption, identified as a major global health risk factor, with epilepsy risk have ... read more 

Portable and intelligent sensor systems are required for real-time air quality monitoring, and among them, the metal-oxide-semiconductor gas sensors are widely used in many scenarios. However, the inconsistency, baseline drifts, and complex off-board... read more 

BACKGROUND AND AIMS: Histological grading of renal cell carcinoma (RCC) is an important part of diagnostic evaluation. Reproducibility of RCC grading using whole-slide imaging (WSI) compared to glass-slide microscopy is understudied. The aim of the s... read more 

OBJECTIVES: To develop and do multicenter validation on an algorithm that screens for osteoporosis from abdominal CTs. METHODS: This is a diagnostic accuracy study with retrospective data from January 2022 to July 2022 consisting of two steps: a segm... read more 

OBJECTIVES: This study aims to develop an artificial intelligence (AI)-based automated segmentation method for small renal masses (SRMs) using multi-center, multi-scanner, multi-sequence MRI data. METHODS: MR images from 988 pathologically confirmed ... read more