AIMC Topic: Diagnosis, Computer-Assisted

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Skin cancer classification leveraging multi-directional compact convolutional neural network ensembles and gabor wavelets.

Scientific reports
Skin cancer (SC) is an important medical condition that necessitates prompt identification to ensure timely treatment. Although visual evaluation by dermatologists is considered the most reliable method, its efficacy is subjective and laborious. Deep...

Use of artificial intelligence improves colonoscopy performance in adenoma detection: a systematic review and meta-analysis.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Artificial intelligence (AI) is increasingly used to improve adenoma detection during colonoscopy. This meta-analysis aimed to provide an updated evaluation of computer-aided detection (CADe) systems and their impact on key colon...

Utilization of an artificial intelligence-enhanced, web-based application to review bile duct brushing cytologic specimens: A pilot study.

Cancer cytopathology
BACKGROUND: The authors previously developed an artificial intelligence (AI) to assist cytologists in the evaluation of digital whole-slide images (WSIs) generated from bile duct brushing specimens. The aim of this trial was to assess the efficiency ...

Computer-aided diagnosis of eyelid skin tumors using machine learning.

Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
OBJECTIVE: To develop an automated, new framework based on machine learning to diagnose malignant eyelid skin tumors.

Towards laryngeal cancer diagnosis using Dandelion Optimizer Algorithm with ensemble learning on biomedical throat region images.

Scientific reports
Laryngeal cancer exhibits a notable global health burden, with later-stage detection contributing to a low mortality rate. Laryngeal cancer diagnosis on throat region images is a pivotal application of computer vision (CV) and medical image diagnoses...

An efficient ANN SoC for detecting Alzheimer's disease based on recurrent computing.

Computers in biology and medicine
Alzheimer's Disease (AD) is an irreversible, degenerative condition that, while incurable, can have its progression slowed or impeded. While there are numerous methods utilizing neural networks for AD detection, there is a scarcity of High-performanc...

An optimized model based on adaptive convolutional neural network and grey wolf algorithm for breast cancer diagnosis.

PloS one
Medical image classification (IC) is a method for categorizing images according to the appropriate pathological stage. It is a crucial stage in computer-aided diagnosis (CAD) systems, which were created to help radiologists with reading and analyzing...

Artificial intelligence-driven electrocardiography: Innovations in hypertrophic cardiomyopathy management.

Trends in cardiovascular medicine
Hypertrophic Cardiomyopathy (HCM) presents a complex diagnostic and prognostic challenge due to its heterogeneous phenotype and clinical course. Artificial Intelligence (AI) and Machine Learning (ML) techniques hold promise in transforming the role o...

Robust ROI Detection in Whole Slide Images Guided by Pathologists' Viewing Patterns.

Journal of imaging informatics in medicine
Deep learning techniques offer improvements in computer-aided diagnosis systems. However, acquiring image domain annotations is challenging due to the knowledge and commitment required of expert pathologists. Pathologists often identify regions in wh...

Reinforced Computer-Aided Framework for Diagnosing Thyroid Cancer.

IEEE/ACM transactions on computational biology and bioinformatics
Thyroid cancer is the most pervasive disease in the endocrine system and is getting extensive attention. The most prevalent method for an early check is ultrasound examination. Traditional research mainly concentrates on promoting the performance of ...