Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 50,421 to 50,430 of 224,814 articles

Class-balanced dermoscopic lesion segmentation using MoG-LISA and optimized Swin-UNet via the GM-FDE framework.

iScience
Automatic skin lesion segmentation is one of the key pivotal tasks in dermatological image processing, with important consequences in early melanoma diagnosis and treatment planning. Nevertheless, issues of extreme class imbalance, morphological vari... read more 

Infrared spectral data of natural and man-made textile fibres for material identification and classification.

Data in brief
This article presents a structured dataset of attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra acquired from natural and man-made textile fibres, compiled to support research in forensic, analytical, and environmental scienc... read more 

Psychological determinants of transport mode choice: A comprehensive dataset from Pabna Municipality, Bangladesh.

Data in brief
This data article introduces a detailed and structured dataset derived from a survey exploring the psychological factors that influence transport mode choices in Pabna Municipality, northwest of Bangladesh. This dataset covers a wide range of socio-d... read more 

Trust - IoV: An open benchmark dataset for trust management in the internet of vehicles.

Data in brief
Whilst advancements in information and communication technologies and artificial intelligence have considerably enhanced the capabilities of the Internet of Vehicles (IoV) paradigm, ensuring the security of this highly dynamic and decentralized netwo... read more 

Enhancing fairness and standardization in AI-versus-physician diagnostic comparisons: A scoping review.

International journal of medical informatics
OBJECTIVE: The growing number of studies directly comparing artificial intelligence (AI) to physicians in diagnostic tasks often focuses on performance outcomes, overlooking fundamental methodological rigor. This scoping review aims to critically app... read more 

Comprehensive study on the performance optimization of hyperspectral unmixing algorithms: A focus on airborne hyperspectral data.

Water research
Hyperspectral imaging technology captures fine-grained spectral information from the Earth's surface, offering transformative potential in fields such as environmental monitoring, agriculture, and defense. Hyperspectral unmixing (HU), which decompose... read more 

Surface-based cortical thickness and gyrification mapping with data-driven prediction of cognitive impairment in prediabetes.

IBRO neuroscience reports
BACKGROUND: Prediabetes is a serious health condition characterized by blood glucose levels that are higher than normal but not high enough for a diagnosis of type 2 diabetes. It remains unclear whether alterations in cortical morphology occur during... read more 

A machine learning approach to predicting clinical trajectories in bipolar disorder.

Psychiatry research
BACKGROUND: Bipolar disorder (BD) is characterized by significant heterogeneity in clinical presentation, age of onset, and diagnostic delays. Identifying clinical trajectories and subtypes is a central aim of precision psychiatry, with the goal of i... read more 

Label-Free rapid bone biomarkers assessment via physics-guided machine learning-assisted photoacoustic correlation spectra analysis.

Ultrasonics
Obtaining information on bone metabolism through intraoperative or non-invasive examination remains a challenge in medical practice. Photoacoustic (PA) spectroscopy offers a method for identifying molecules within biological tissues by exploiting the... read more 

Future nurses' attitudes and anxiety toward artificial intelligence: A cross-sectional study.

Nurse education today
AIM: This study aimed to examine the relationship between nursing students' attitudes toward artificial intelligence (AI) and their levels of AI-related anxiety. BACKGROUND: The rapid integration of AI into healthcare requires nursing students to und... read more