AIMC Topic: Diagnosis, Computer-Assisted
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Severity grading of hypertensive retinopathy using hybrid deep learning architecture.
Computer methods and programs in biomedicine
Jan 15, 2025
BACKGROUND AND OBJECTIVES: Hypertensive Retinopathy (HR) is a retinal manifestation resulting from persistently elevated blood pressure. Severity grading of HR is essential for patient risk stratification, effective management, progression monitoring...
Colorectal cancer classification using weakly annotated whole slide images: Multiple instance learning optimization study.
Computers in biology and medicine
Jan 10, 2025
Colorectal cancer (CRC) is considered one of the most deadly cancer types nowadays. It is rapidly increasing due to many factors, such as unhealthy lifestyles, water and food pollution, aging, and medical diagnosis development. Detecting CRC in its e...
Residual-attention deep learning model for atrial fibrillation detection from Holter recordings.
Journal of electrocardiology
Jan 10, 2025
BACKGROUND: Detecting subtle patterns of atrial fibrillation (AF) and irregularities in Holter recordings is intricate and unscalable if done manually. Artificial intelligence-based techniques can be beneficial. In fact, with the rapid advancement of...
The importance of clinical experience in AI-assisted corneal diagnosis: verification using intentional AI misleading.
Scientific reports
Jan 9, 2025
We developed an AI system capable of automatically classifying anterior eye images as either normal or indicative of corneal diseases. This study aims to investigate the influence of AI's misleading guidance on ophthalmologists' responses. This cross...
Machine learning-derived asthma and allergy trajectories in children: a systematic review and meta-analysis.
European respiratory review : an official journal of the European Respiratory Society
Jan 8, 2025
INTRODUCTION: Numerous studies have characterised trajectories of asthma and allergy in children using machine learning, but with different techniques and mixed findings. The present work aimed to summarise the evidence and critically appraise the me...
Computer-aided diagnosis of hepatic cystic echinococcosis based on deep transfer learning features from ultrasound images.
Scientific reports
Jan 3, 2025
Hepatic cystic echinococcosis (HCE), a life-threatening liver disease, has 5 subtypes, i.e., single-cystic, polycystic, internal capsule collapse, solid mass, and calcified subtypes. And each subtype has different treatment methods. An accurate diagn...
Automated CAD system for early detection and classification of pancreatic cancer using deep learning model.
PloS one
Jan 3, 2025
Accurate diagnosis of pancreatic cancer using CT scan images is critical for early detection and treatment, potentially saving numerous lives globally. Manual identification of pancreatic tumors by radiologists is challenging and time-consuming due t...
HistoColAi: An open-source web platform for collaborative digital histology image annotation with AI-driven predictive integration.
Computer methods and programs in biomedicine
Jan 1, 2025
Digital pathology is now a standard component of the pathology workflow, offering numerous benefits such as high-detail whole slide images and the capability for immediate case sharing between hospitals. Recent advances in deep learning-based methods...
A novel lightweight deep learning based approaches for the automatic diagnosis of gastrointestinal disease using image processing and knowledge distillation techniques.
Computer methods and programs in biomedicine
Dec 30, 2024
BACKGROUND: Gastrointestinal (GI) diseases pose significant challenges for healthcare systems, largely due to the complexities involved in their detection and treatment. Despite the advancements in deep neural networks, their high computational deman...
Diagnosis of Autism Spectrum Disorder (ASD) by Dynamic Functional Connectivity Using GNN-LSTM.
Sensors (Basel, Switzerland)
Dec 30, 2024
Early detection of autism spectrum disorder (ASD) is particularly important given its insidious qualities and the high cost of the diagnostic process. Currently, static functional connectivity studies have achieved significant results in the field of...
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