AIMC Topic: Humans

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Machine learning for predicting cognitive deficits using auditory and demographic factors.

PloS one
IMPORTANCE: Predicting neurocognitive deficits using complex auditory assessments could change how cognitive dysfunction is identified, and monitored over time. Detecting cognitive impairment in people living with HIV (PLWH) is important for early in...

Accuracy of artificial intelligence-assisted endoscopy in the diagnosis of gastric intestinal metaplasia: A systematic review and meta-analysis.

PloS one
BACKGROUND AND AIMS: Gastric intestinal metaplasia is a precancerous disease, and a timely diagnosis is essential to delay or halt cancer progression. Artificial intelligence (AI) has found widespread application in the field of disease diagnosis. Th...

A hybrid CNN-SVM model for enhanced autism diagnosis.

PloS one
Autism is a representative disorder of pervasive developmental disorder. It exerts influence upon an individual's behavior and performance, potentially co-occurring with other mental illnesses. Consequently, an effective diagnostic approach proves to...

Natural language sentiment as an indicator of depression and anxiety symptoms: a longitudinal mixed methods study.

Cognition & emotion
The study tested how the use of positive- (e.g. beautiful) and negative-valenced (e.g. horrible) words in natural language and its change in time affects the severity of depression and anxiety symptoms among depressed and non-depressed individuals. T...

An Exaggeration? Reality?: Can ChatGPT Be Used in Neonatal Nursing?

The Journal of perinatal & neonatal nursing
Artificial intelligence (AI) represents a system endowed with the ability to derive meaningful inferences from a diverse array of datasets. Rooted in the advancements of machine learning models, AI has spawned various transformative technologies such...

Deep Learning-Based Detect-Then-Track Pipeline for Treatment Outcome Assessments in Immunotherapy-Treated Liver Cancer.

Journal of imaging informatics in medicine
Accurate treatment outcome assessment is crucial in clinical trials. However, due to the image-reading subjectivity, there exist discrepancies among different radiologists. The situation is common in liver cancer due to the complexity of abdominal sc...

Robust prostate disease classification using transformers with discrete representations.

International journal of computer assisted radiology and surgery
PURPOSE: Automated prostate disease classification on multi-parametric MRI has recently shown promising results with the use of convolutional neural networks (CNNs). The vision transformer (ViT) is a convolutional free architecture which only exploit...

Comparison of 21 artificial intelligence algorithms in automated diabetic retinopathy screening using handheld fundus camera.

Annals of medicine
BACKGROUND: Diabetic retinopathy (DR) is a common complication of diabetes and may lead to irreversible visual loss. Efficient screening and improved treatment of both diabetes and DR have amended visual prognosis for DR. The number of patients with ...

Dynamic mirroring: unveiling the role of digital twins, artificial intelligence and synthetic data for personalized medicine in laboratory medicine.

Clinical chemistry and laboratory medicine
In recent years, the integration of technological advancements and digitalization into healthcare has brought about a remarkable transformation in care delivery and patient management. Among these advancements, the concept of digital twins (DTs) has ...