AI Medical Compendium Topic

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Diagnosis, Differential

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Application of convolutional neural network for differentiating ovarian thecoma-fibroma and solid ovarian cancer based on MRI.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Ovarian thecoma-fibroma and solid ovarian cancer have similar clinical and imaging features, and it is difficult for radiologists to differentiate them. Since the treatment and prognosis of them are different, accurate characterization is...

Discriminative diagnosis of ovarian endometriosis cysts and benign mucinous cystadenomas based on the ConvNeXt algorithm.

European journal of obstetrics, gynecology, and reproductive biology
PURPOSE: The objective of this study was to develop a deep learning model, using the ConvNeXt algorithm, that can effectively differentiate between ovarian endometriosis cysts (OEC) and benign mucinous cystadenomas (MC) by analyzing ultrasound images...

The diagnostic performance of AI-based algorithms to discriminate between NMOSD and MS using MRI features: A systematic review and meta-analysis.

Multiple sclerosis and related disorders
BACKGROUND: Magnetic resonance imaging [MRI] findings in Neuromyelitis optica spectrum disorder [NMOSD] and Multiple Sclerosis [MS] patients could lead us to discriminate toward them. For instance, U-fiber and Dawson's finger-type lesions are suggest...

Development and Application of Traditional Chinese Medicine Using AI Machine Learning and Deep Learning Strategies.

The American journal of Chinese medicine
Traditional Chinese medicine (TCM) has been used for thousands of years and has been proven to be effective at treating many complicated illnesses with minimal side effects. The application and advancement of TCM are, however, constrained by the abse...

New perspectives in the differential diagnosis of jaw lesions: Machine learning and inflammatory biomarkers.

Journal of stomatology, oral and maxillofacial surgery
This study aimed to assess the diagnostic performance of a machine learning approach that utilized radiomic features extracted from Cone Beam Computer Tomography (CBCT) images and inflammatory biomarkers for distinguishing between Dentigerous Cysts (...

Computerized diagnostic decision support systems - a comparative performance study of Isabel Pro vs. ChatGPT4.

Diagnosis (Berlin, Germany)
OBJECTIVES: Validate the diagnostic accuracy of the Artificial Intelligence Large Language Model ChatGPT4 by comparing diagnosis lists produced by ChatGPT4 to Isabel Pro.

Precise and automated lung cancer cell classification using deep neural network with multiscale features and model distillation.

Scientific reports
Lung diseases globally impose a significant pathological burden and mortality rate, particularly the differential diagnosis between adenocarcinoma, squamous cell carcinoma, and small cell lung carcinoma, which is paramount in determining optimal trea...

A novel multidisciplinary machine learning approach based on clinical, imaging, colonoscopy, and pathology features for distinguishing intestinal tuberculosis from Crohn's disease.

Abdominal radiology (New York)
OBJECTIVES: Differentiating intestinal tuberculosis (ITB) from Crohn's disease (CD) remains a diagnostic dilemma. Misdiagnosis carries potential grave implications. We aim to establish a multidisciplinary-based model using machine learning approach f...

A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma.

Nature communications
Accurate intraoperative differentiation of primary central nervous system lymphoma (PCNSL) remains pivotal in guiding neurosurgical decisions. However, distinguishing PCNSL from other lesions, notably glioma, through frozen sections challenges pathol...