[HTML][HTML] A comprehensive survey of deep learning algorithms and applications in dental radiograph analysis

S Bhat, GK Birajdar, MD Patil - Healthcare Analytics, 2023 - Elsevier
The Integration of machine learning and traditional image processing in dentistry has
resulted in many applications like automatic teeth identification and numbering, caries …

Revolutionizing Healthcare: How Machine Learning is Transforming Patient Diagnoses-a Comprehensive Review of AI's Impact on Medical Diagnosis

AY Gill, A Saeed, S Rasool, A Husnain… - Journal of World …, 2023 - jws.rivierapublishing.id
The integration of machine learning into healthcare heralds a new era where the
convergence of technology and human compassion reshapes the very essence of healing …

Intelligent ultrasound imaging for enhanced breast cancer diagnosis: Ensemble transfer learning strategies

KS Rao, PV Terlapu, D Jayaram, KK Raju… - IEEE …, 2024 - ieeexplore.ieee.org
According to WHO statistics for 2018, there are 1.2 million cases and 700,000 deaths from
breast cancer (BC) each year, making it the second-highest cause of mortality for women …

Multistage transfer learning for medical images

G Ayana, K Dese, AM Abagaro, KC Jeong… - Artificial Intelligence …, 2024 - Springer
Deep learning is revolutionizing various domains and significantly impacting medical image
analysis. Despite notable progress, numerous challenges remain, necessitating the …

Graph convolution networks for social media trolls detection use deep feature extraction

M Asif, M Al-Razgan, YA Ali, L Yunrong - Journal of Cloud Computing, 2024 - Springer
This study presents a novel approach to identifying trolls and toxic content on social media
using deep learning. We developed a machine-learning model capable of detecting toxic …

Novel transfer learning based deep features for diagnosis of down syndrome in children using facial images

A Raza, K Munir, MS Almutairi, R Sehar - IEEE Access, 2024 - ieeexplore.ieee.org
Down syndrome is a chromosomal condition characterized by the existence of an additional
copy of chromosome 21. This genetic anomaly leads to a range of developmental …

A novel hybrid model in the diagnosis and classification of Alzheimer's disease using EEG signals: Deep ensemble learning (DEL) approach

M Nour, U Senturk, K Polat - Biomedical Signal Processing and Control, 2024 - Elsevier
Recent years have witnessed a surge of sophisticated computer-aided diagnosis techniques
involving Artificial Intelligence (AI) to accurately diagnose and classify Alzheimer's disease …

An adaptation of hybrid binary optimization algorithms for medical image feature selection in neural network for classification of breast cancer

ON Oyelade, EF Aminu, H Wang, K Rafferty - Neurocomputing, 2025 - Elsevier
The performance of neural network is largely dependent on their capability to extract very
discriminant features supporting the characterization of abnormalities in the medical image …

Intraoperative detection of parathyroid glands using artificial intelligence: optimizing medical image training with data augmentation methods

JH Lee, EK Ku, YS Chung, YJ Kim, KG Kim - Surgical Endoscopy, 2024 - Springer
Background Postoperative hypoparathyroidism is a major complication of thyroidectomy,
occurring when the parathyroid glands are inadvertently damaged during surgery. Although …

CViTS-Net: A CNN-ViT Network with Skip Connections for Histopathology Image Classification

A Kanadath, JAA Jothi, S Urolagin - IEEE Access, 2024 - ieeexplore.ieee.org
Histopathological image classification stands as a cornerstone in the pathological diagnosis
workflow, yet it remains challenging due to the inherent complexity of histopathological …