AIMC Topic: Deep Learning

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Development of an efficient novel method for coronary artery disease prediction using machine learning and deep learning techniques.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Heart disease is a severe health issue that results in high fatality rates worldwide. Identifying cardiovascular diseases such as coronary artery disease (CAD) and heart attacks through repetitive clinical data analysis is a significant t...

A hybrid model for the classification of Autism Spectrum Disorder using Mu rhythm in EEG.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Autism Spectrum Disorder (ASD) is a condition with social interaction, communication, and behavioral difficulties. Diagnostic methods mostly rely on subjective evaluations and can lack objectivity. In this research Machine learning (ML) a...

Gastrointestinal tract disease detection via deep learning based structural and statistical features optimized hexa-classification model.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Gastrointestinal tract (GIT) diseases impact the entire digestive system, spanning from the mouth to the anus. Wireless Capsule Endoscopy (WCE) stands out as an effective analytic instrument for Gastrointestinal tract diseases. Neverthele...

CNN-based glioma detection in MRI: A deep learning approach.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: More than a million people are affected by brain tumors each year; high-grade gliomas (HGGs) and low-grade gliomas (LGGs) present serious diagnostic and treatment hurdles, resulting in shortened life expectancies. Glioma segmentation is s...

Automated cutaneous squamous cell carcinoma grading using deep learning with transfer learning.

Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie
INTRODUCTION: Histological grading of cutaneous squamous cell carcinoma (cSCC) is crucial for prognosis and treatment decisions, but manual grading is subjective and time-consuming.

Analysis of pig posture detection in group-housed pigs using deep learning-based mask scoring instance segmentation.

Animal science journal = Nihon chikusan Gakkaiho
Pig posture is closely linked with livestock health and welfare. There has been significant interest among researchers in using deep learning techniques for pig posture detection. However, this task is challenging due to variations in image angles an...

Screening Targets and Therapeutic Drugs for Alzheimer's Disease Based on Deep Learning Model and Molecular Docking.

Journal of Alzheimer's disease : JAD
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder caused by a complex interplay of various factors. However, a satisfactory cure for AD remains elusive. Pharmacological interventions based on drug targets are considered the most co...

Assessment of Protein-Protein Docking Models Using Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Protein-protein interactions are involved in almost all processes in a living cell and determine the biological functions of proteins. To obtain mechanistic understandings of protein-protein interactions, the tertiary structures of protein complexes ...

Artificial intelligence's contribution to early pulmonary lesion detection in chest X-rays: insights from two retrospective studies on a Czech population.

Casopis lekaru ceskych
In recent years healthcare is undergoing significant changes due to technological innovations, with Artificial Intelligence (AI) being a key trend. Particularly in radiodiagnostics, according to studies, AI has the potential to enhance accuracy and e...

Artificial intelligence in medicine and healthcare: Opportunity and/or threat.

Casopis lekaru ceskych
The aim of the article to present the development of artificial intelligence (AI) methods and their applications in medicine and health care. Current technological development contributes to generation of large volumes of data that cannot be evaluate...