AI Medical Compendium Topic

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Diagnosis, Computer-Assisted

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Breast Cancer Tissue Classification from Multiple Annotators using Chained Deep Learning Approaches.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Breast cancer is one of the principal causes of cancer death worldwide. The biopsy diagnosis is non-trivial, and specialists often disagree on the final diagnosis. Thus, Computer-aided Diagnosis-(CAD) systems favor the efficiency of this process whil...

Diagnosis of Pneumoconiosis with Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Pneumoconiosis encompasses a group of lung diseases caused by inhaling dust particles. Frequently recognized as an occupational disease, it primarily affects workers in the mining industry. This paper details the use of machine learning algorithms to...

Dynamic multi-hypergraph structure learning for disease diagnosis on multimodal data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
With its superior capability in complex data modeling, hypergraph computation is a powerful tool for many applications. In this work, we propose using hypergraph computation for disease prediction. Hypergraphs allow for the representation of higher-o...

LightIED: Explainable AI with Light CNN for Interictal Epileptiform Discharge Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Interictal epileptic discharge (IED) detection from electroencephalography (EEG) is an important but difficult step in the epilepsy diagnosis. To reduce the workload of doctors, some diagnostic auxiliary methods based on deep learning have been propo...

Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
While deep learning methods are increasingly applied in research contexts for neuropsychiatric disorder diagnosis, small dataset size limits their potential for clinical translation. Data augmentation (DA) could address this limitation, but the utili...

A nested cross validation approach to machine learning model performance evaluation on a small dataset for Creutzfeldt-Jakob disease diagnosis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The use of machine learning (ML) to diagnose neurological diseases has become increasingly popular. However, some rare neurodegenerative diseases such as Creutzfeldt-Jakob disease (CJD) suffer from the way that the traditional diagnosis relying abnor...

A comparative analysis of Constant-Q Transform, gammatonegram, and Mel-spectrogram techniques for AI-aided cardiac diagnostics.

Medical engineering & physics
Cardiovascular diseases (CVDs) are the leading global cause of death, which requires the early and accurate detection of cardiac abnormalities. Abnormal heart sounds, indicative of potential cardiac problems, pose a challenge due to their low-frequen...

FEGGNN: Feature-Enhanced Gated Graph Neural Network for robust few-shot skin disease classification.

Computers in biology and medicine
Accurate and timely classification of skin diseases is essential for effective dermatological diagnosis. However, the limited availability of annotated images, particularly for rare or novel conditions, poses a significant challenge. Although few-sho...

Development and validation of computer-aided detection for colorectal neoplasms using deep learning incorporated with computed tomography colonography.

BMC gastroenterology
OBJECTIVES: Computed tomography (CT) colonography is increasingly recognized as a valuable modality for diagnosing colorectal lesions, however, the interpretation workload remains challenging for physicians. Deep learning-based artificial intelligenc...