AIMC Topic: Diagnosis, Computer-Assisted

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A practical approach for colorectal cancer diagnosis based on machine learning.

PloS one
In this paper, we present the results of applying machine learning models to build a Colorectal Cancer Diagnosis system. The methodology encompasses six key steps: collecting raw data from Electronic Medical Records (EMRs), revising feature attribute...

Enhanced glaucoma classification through advanced segmentation by integrating cup-to-disc ratio and neuro-retinal rim features.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Glaucoma is a progressive eye condition caused by high intraocular fluid pressure, damaging the optic nerve, leading to gradual, irreversible vision loss, often without noticeable symptoms. Subtle signs like mild eye redness, slightly blurred vision,...

Single-View Contrastive Learning for Laryngeal Leukoplakia Classification With NBI Laryngoscopy Images.

Head & neck
BACKGROUND: Laryngeal cancer is the second most common upper respiratory tract cancer. Early and accurate diagnosis can improve the cure rate of patients. Laryngoscopy with NBI is a commonly used tool that can help endoscopists diagnose laryngeal dis...

Artificial Intelligence in Diagnosis of Heart Failure.

Journal of the American Heart Association
Heart failure (HF) is a complex and varied condition that affects over 50 million people worldwide. Although there have been significant strides in understanding the underlying mechanisms of HF, several challenges persist, particularly in the accurat...

One-class support vector machines for detecting population drift in deployed machine learning medical diagnostics.

Scientific reports
Machine learning (ML) models are increasingly being applied to diagnose and predict disease, but face technical challenges such as population drift, where the training and real-world deployed data distributions differ. This phenomenon can degrade mod...

ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

BMC cardiovascular disorders
A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly imp...

Enhancing breast cancer diagnosis: transfer learning on DenseNet with neural hashing for histopathology fine-grained image classification.

Medical & biological engineering & computing
Breast cancer is one of the most common types of cancer worldwide. The number of breast cancer cases highlights the importance of disease management at various levels. One complementary method for breast cancer classification is microscopic imaging. ...

Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High-Risk Adenomas Among Colorectal Polyps 10 mm or Smaller.

Journal of digestive diseases
OBJECTIVE: This study aimed to develop a computer-aided diagnosis (CADx) model using an automated deep learning (DL) program to classify low- and high-risk adenomas among colorectal polyps ≤ 10 mm with standard white-light endoscopy.

Computer-assisted diagnosis to improve diagnostic pathology: A review.

Indian journal of pathology & microbiology
With an increasing demand for accuracy and efficiency in diagnostic pathology, computer-assisted diagnosis (CAD) emerges as a prominent and transformative solution. This review aims to explore the practical applications, implications, strengths, and ...

Explainable AI-based feature importance analysis for ovarian cancer classification with ensemble methods.

Frontiers in public health
INTRODUCTION: Ovarian Cancer (OC) is one of the leading causes of cancer deaths among women. Despite recent advances in the medical field, such as surgery, chemotherapy, and radiotherapy interventions, there are only marginal improvements in the diag...