AIMC Topic: Humans

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Dissatisfaction-considered waiting time prediction for outpatients with interpretable machine learning.

Health care management science
Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim to analytically interpret the waiting times predicted by machine learning models and provide patients with an explanation of the expected waiting time....

Alterations in dynamic regional homogeneity within default mode network in patients with thyroid-associated ophthalmopathy.

Neuroreport
Thyroid-associated ophthalmopathy (TAO) is a significant autoimmune eye disease known for causing exophthalmos and substantial optic nerve damage. Prior investigations have solely focused on static functional MRI (fMRI) scans of the brain in TAO pati...

Machine learning-based model for predicting outcomes in cerebral hemorrhage patients with leukemia.

European journal of radiology
BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) in leukemia patients progresses rapidly with high mortality. Limited data are available on imaging studies in this population. The study aims to develop prediction models for 7-day and short-term ...

EEG based functional connectivity in resting and emotional states may identify major depressive disorder using machine learning.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Disrupted brain network connectivity underlies major depressive disorder (MDD). Altered EEG based Functional connectivity (FC) with Emotional stimuli in major depressive disorder (MDD) in addition to resting state FC may help in improving ...

Assessment of an AI-based tool for population-wide collection of placental morphological data.

European journal of obstetrics, gynecology, and reproductive biology
OBJECTIVES: Automated placental assessment could allow accurate and timely morphological/pathological measurements at scale. We undertook a pilot study using an artificial intelligence-based assessment system (AI-PLAX) to ascertain the potential of a...

What makes a good scientific presentation on artificial intelligence in medical imaging?

Clinical imaging
PURPOSE: Adequate communication of scientific findings is crucial to enhance knowledge transfer. This study aimed to determine the key features of a good scientific oral presentation on artificial intelligence (AI) in medical imaging.

Deep Learning for Histopathological Assessment of Esophageal Adenocarcinoma Precursor Lesions.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Histopathological assessment of esophageal biopsies is a key part in the management of patients with Barrett esophagus (BE) but prone to observer variability and reliable diagnostic methods are needed. Artificial intelligence (AI) is emerging as a po...

The Role and Applications of Artificial Intelligence in the Treatment of Chronic Pain.

Current pain and headache reports
PURPOSE OF REVIEW: This review aims to explore the interface between artificial intelligence (AI) and chronic pain, seeking to identify areas of focus for enhancing current treatments and yielding novel therapies.

Integrated analysis of multiple transcriptomic approaches and machine learning integration algorithms reveals high endothelial venules as a prognostic immune-related biomarker in bladder cancer.

International immunopharmacology
BACKGROUND: Despite the availability of established surgical and chemotherapy options, the treatment of bladder cancer (BCa) patients remains challenging. While immunotherapy has emerged as a promising approach, its benefits are limited to a subset o...