AIMC Topic: Humans

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Molecular Indicator for Distinguishing Multi-drug-Resistant Tuberculosis from Drug Sensitivity Tuberculosis and Potential Medications for Treatment.

Molecular biotechnology
The issue of multi-drug-resistant tuberculosis (MDR-TB) presents a substantial challenge to global public health. Regrettably, the diagnosis of drug-resistant tuberculosis (DR-TB) frequently necessitates an extended period or more extensive laborator...

Patient-Specific Deep Learning Tracking Framework for Real-Time 2D Target Localization in Magnetic Resonance Imaging-Guided Radiation Therapy.

International journal of radiation oncology, biology, physics
PURPOSE: We propose a tumor tracking framework for 2D cine magnetic resonance imaging (MRI) based on a pair of deep learning (DL) models relying on patient-specific (PS) training.

Editorial Commentary: Studies Evaluating Artificial Intelligence Large Language Models' Ability to Respond to Questions Are Repetitive and Out-of-Date: Artificial Intelligence Must Now Be Applied to Improve Clinical Practice and Patient Care.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
While artificial intelligence (AI) technologies such as ChatGPT have shown very real and powerful capabilities to date, this does not mean that research studying these technologies is immune from "shiny object syndrome," a psychological phenomenon in...

Integrating VAI-Assisted Quantified CXRs and Multimodal Data to Assess the Risk of Mortality.

Journal of imaging informatics in medicine
To address the unmet need for a widely available examination for mortality prediction, this study developed a foundation visual artificial intelligence (VAI) to enhance mortality risk stratification using chest X-rays (CXRs). The VAI employed deep le...

A comparative analysis of unsupervised machine-learning methods in PSG-related phenotyping.

Journal of sleep research
Obstructive sleep apnea is a heterogeneous sleep disorder with varying phenotypes. Several studies have already performed cluster analyses to discover various obstructive sleep apnea phenotypic clusters. However, the selection of the clustering metho...

Increasing transparency of computer-aided detection impairs decision-making in visual search.

Psychonomic bulletin & review
Recent developments in artificial intelligence (AI) have led to changes in healthcare. Government and regulatory bodies have advocated the need for transparency in AI systems with recommendations to provide users with more details about AI accuracy a...

A novel endoscopic artificial intelligence system to assist in the diagnosis of autoimmune gastritis: a multicenter study.

Endoscopy
BACKGROUND:  Autoimmune gastritis (AIG), distinct from Helicobacter pylori-associated atrophic gastritis (HpAG), is underdiagnosed due to limited awareness. This multicenter study aimed to develop a novel endoscopic artificial intelligence (AI) syste...

An explainable machine learning estimated biological age based on morphological parameters of the spine.

GeroScience
Accurately estimating biological age is beneficial for measuring aging and predicting risk. It is widely accepted that the prevalence of spine compression increases significantly with age. However, biological age based on vertebral morphological data...

An optimized siamese neural network with deep linear graph attention model for gynaecological abdominal pelvic masses classification.

Abdominal radiology (New York)
An adnexal mass, also known as a pelvic mass, is a growth that develops in or near the uterus, ovaries, fallopian tubes, and supporting tissues. For women suspected of having ovarian cancer, timely and accurate detection of a malignant pelvic mass is...