AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Diagnosis, Computer-Assisted

Showing 261 to 270 of 1683 articles

Clear Filters

Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive Learning.

IEEE transactions on medical imaging
Well-annotated medical datasets enable deep neural networks (DNNs) to gain strong power in extracting lesion-related features. Building such large and well-designed medical datasets is costly due to the need for high-level expertise. Model pre-traini...

A multi-stage fusion framework to classify breast lesions using deep learning and radiomics features computed from four-view mammograms.

Medical physics
BACKGROUND: Developing computer aided diagnosis (CAD) schemes of mammograms to classify between malignant and benign breast lesions has attracted a lot of research attention over the last several decades. However, unlike radiologists who make diagnos...

A Novel Deep-Learning-Based CADx Architecture for Classification of Thyroid Nodules Using Ultrasound Images.

Interdisciplinary sciences, computational life sciences
Nodules of thyroid cancer occur in the cells of the thyroid as benign or malign types. Thyroid sonographic images are mostly used for diagnosis of thyroid cancer. The aim of this study is to introduce a computer-aided diagnosis system that can classi...

Diagnosis of liver diseases based on artificial intelligence.

Biotechnology & genetic engineering reviews
Due to a series of problems in the diagnosis of liver disease, the mortality rate of liver disease patients is very high. Therefore, it is necessary for doctors and researchers to find a more effective non-invasive diagnostic method to meet clinical ...

Comparative study of convolutional neural network architectures for gastrointestinal lesions classification.

PeerJ
The gastrointestinal (GI) tract can be affected by different diseases or lesions such as esophagitis, ulcers, hemorrhoids, and polyps, among others. Some of them can be precursors of cancer such as polyps. Endoscopy is the standard procedure for the ...

Diagnostic accuracy of AI in orthodontic extraction decisions: "Are we ready to let Mr. Data run our Enterprise?" A commentary on a systematic review.

Evidence-based dentistry
OBJECTIVE: To collect evidence on the ability of artificial intelligence programs to accurately make extraction decisions in orthodontic treatment planning.

A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography.

Sensors (Basel, Switzerland)
In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delicate to diag...

Automated postural asymmetry assessment in infants neurodevelopmental evaluation using novel video-based features.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Neurodevelopmental assessment enables the identification of infant developmental disorders in the first months of life. Thus, the appropriate therapy can be initiated promptly, increasing the chances for correct motor functi...

EBHI: A new Enteroscope Biopsy Histopathological H&E Image Dataset for image classification evaluation.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND AND PURPOSE: Colorectal cancer has become the third most common cancer worldwide, accounting for approximately 10% of cancer patients. Early detection of the disease is important for the treatment of colorectal cancer patients. Histopathol...

PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Open-source deep learning toolkits are one of the driving forces for developing medical image segmentation models that are essential for computer-assisted diagnosis and treatment procedures. Existing toolkits mainly focus on...