AI Medical Compendium Topic

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Diagnosis, Computer-Assisted

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An open codebase for enhancing transparency in deep learning-based breast cancer diagnosis utilizing CBIS-DDSM data.

Scientific reports
Accessible mammography datasets and innovative machine learning techniques are at the forefront of computer-aided breast cancer diagnosis. However, the opacity surrounding private datasets and the unclear methodology behind the selection of subset im...

A lightweight deep-learning model for parasite egg detection in microscopy images.

Parasites & vectors
BACKGROUND: Intestinal parasitic infections are still a serious public health problem in developing countries, and the diagnosis of parasitic infections requires the first step of parasite/egg detection of samples. Automated detection can eliminate t...

Multimodal Machine Learning for Stroke Prognosis and Diagnosis: A Systematic Review.

IEEE journal of biomedical and health informatics
Stroke is a life-threatening medical condition that could lead to mortality or significant sensorimotor deficits. Various machine learning techniques have been successfully used to detect and predict stroke-related outcomes. Considering the diversity...

Uncertainty-Aware Health Diagnostics via Class-Balanced Evidential Deep Learning.

IEEE journal of biomedical and health informatics
Uncertainty quantification is critical for ensuring the safety of deep learning-enabled health diagnostics, as it helps the model account for unknown factors and reduces the risk of misdiagnosis. However, existing uncertainty quantification studies o...

Decoding the black box: Explainable AI (XAI) for cancer diagnosis, prognosis, and treatment planning-A state-of-the art systematic review.

International journal of medical informatics
OBJECTIVE: Explainable Artificial Intelligence (XAI) is increasingly recognized as a crucial tool in cancer care, with significant potential to enhance diagnosis, prognosis, and treatment planning. However, the holistic integration of XAI across all ...

Artificial intelligence-aided colonoscopic differential diagnosis between Crohn's disease and gastrointestinal tuberculosis.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Differentiating between Crohn's disease (CD) and gastrointestinal tuberculosis (GITB) is challenging. We aimed to evaluate the clinical applicability of an artificial intelligence (AI) model for this purpose.

CAD-PsorNet: deep transfer learning for computer-assisted diagnosis of skin psoriasis.

Scientific reports
Psoriasis, being a chronic, inflammatory, lifelong skin disorder, has become a major threat to the human population. The precise and effective diagnosis of psoriasis continues to be difficult for clinicians due to its varied nature. In northern India...

Transformative artificial intelligence in gastric cancer: Advancements in diagnostic techniques.

Computers in biology and medicine
Gastric cancer represents a significant global health challenge with elevated incidence and mortality rates, highlighting the need for advancements in diagnostic and therapeutic strategies. This review paper addresses the critical need for a thorough...

Past, Present, and Future: A History Lesson in Artificial Intelligence.

Gastrointestinal endoscopy clinics of North America
Over the past 5 decades, artificial intelligence (AI) has evolved rapidly. Moving from basic models to advanced machine learning and deep learning systems, the impact of AI on various fields, including medicine, has been profound. In gastroenterology...

A Recognition System for Diagnosing Salivary Gland Neoplasms Based on Vision Transformer.

The American journal of pathology
Salivary gland neoplasms (SGNs) represent a group of human neoplasms characterized by a remarkable cytomorphologic diversity, which frequently poses diagnostic challenges. Accurate histologic categorization of salivary gland tumors is crucial to make...