AIMC Topic: Case-Control Studies

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Differentiating ischemic stroke patients from healthy subjects using a large-scale, retrospective EEG database and machine learning methods.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presenting with ischemic stroke from a healthy cohort of subjects. The model relies on a 3-min resting electroencephalogram (EEG) recording from which featu...

Intelligent classification of major depressive disorder using rs-fMRI of the posterior cingulate cortex.

Journal of affective disorders
Major Depressive Disorder (MDD) is a widespread psychiatric condition that affects a significant portion of the global population. The classification and diagnosis of MDD is crucial for effective treatment. Traditional methods, based on clinical asse...

Discrimination between healthy participants and people with panic disorder based on polygenic scores for psychiatric disorders and for intermediate phenotypes using machine learning.

The Australian and New Zealand journal of psychiatry
OBJECTIVE: Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic di...

Exploring Cognitive Dysfunction in Long COVID Patients: Eye Movement Abnormalities and Frontal-Subcortical Circuits Implications via Eye-Tracking and Machine Learning.

The American journal of medicine
BACKGROUND: Cognitive dysfunction is regarded as one of the most severe aftereffects following coronavirus disease 2019 (COVID-19). Eye movements, controlled by several brain areas, such as the dorsolateral prefrontal cortex and frontal-thalamic circ...

Rapid Endoscopic Diagnosis of Benign Ulcerative Colorectal Diseases With an Artificial Intelligence Contextual Framework.

Gastroenterology
BACKGROUND & AIMS: Benign ulcerative colorectal diseases (UCDs) such as ulcerative colitis, Crohn's disease, ischemic colitis, and intestinal tuberculosis share similar phenotypes with different etiologies and treatment strategies. To accurately diag...

Artificial intelligence facial recognition system for diagnosis of endocrine and metabolic syndromes based on a facial image database.

Diabetes & metabolic syndrome
AIM: To build a facial image database and to explore the diagnostic efficacy and influencing factors of the artificial intelligence-based facial recognition (AI-FR) system for multiple endocrine and metabolic syndromes.

Explainable artificial intelligence models for predicting risk of suicide using health administrative data in Quebec.

PloS one
Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. Artificial intelligence (AI) and machine learning (ML) have emerged to harness large-scale datasets to enhance risk detection. In order to trust and ac...

Machine Learning Model Based on Radiomics for Preoperative Differentiation of Jaw Cystic Lesions.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: This study aims to use machine learning techniques together with radiomics methods to build a preoperative predictive diagnostic model from spiral computed tomography (CT) images. The model is intended for the differential diagnosis of com...

Recognition of Glaucomatous Fundus Images Using Machine Learning Methods Based on Optic Nerve Head Topographic Features.

Journal of glaucoma
PRCIS: Machine learning classifiers are an effective approach to detecting glaucomatous fundus images based on optic disc topographic features making it a straightforward and effective approach.

Impact of artificial intelligence arrhythmia mapping on time to first ablation, procedure duration, and fluoroscopy use.

Journal of cardiovascular electrophysiology
INTRODUCTION: Artificial intelligence (AI) ECG arrhythmia mapping provides arrhythmia source localization using 12-lead ECG data; whether this information impacts procedural efficiency is unknown. We performed a retrospective, case-control study to e...