AI Medical Compendium Topic

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Diagnosis, Differential

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Accurate stratification between VEXAS syndrome and differential diagnoses by deep learning analysis of peripheral blood smears.

Clinical chemistry and laboratory medicine
OBJECTIVES: VEXAS syndrome is a newly described autoinflammatory disease associated with somatic mutations and vacuolization of myeloid precursors. This disease possesses an increasingly broad spectrum, leading to an increase in the number of suspec...

Deep Learning for Differentiation of Breast Masses Detected by Screening Ultrasound Elastography.

Ultrasound in medicine & biology
Recently, deep learning using convolutional neural networks (CNNs) has yielded consistent results in image-pattern recognition. This study was aimed at investigating the effectiveness of deep learning using CNNs to differentiate benign and malignant ...

Differential diagnosis of prostate cancer and benign prostatic hyperplasia based on DCE-MRI using bi-directional CLSTM deep learning and radiomics.

Medical & biological engineering & computing
Dynamic contrast-enhanced MRI (DCE-MRI) is routinely included in the prostate MRI protocol for a long time; its role has been questioned. It provides rich spatial and temporal information. However, the contained information cannot be fully extracted ...

Machine Learning and Non-Affective Psychosis: Identification, Differential Diagnosis, and Treatment.

Current psychiatry reports
PURPOSE OF REVIEW: This review will cover the most relevant findings on the use of machine learning (ML) techniques in the field of non-affective psychosis, by summarizing the studies published in the last three years focusing on illness detection an...

Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging.

BMC medical informatics and decision making
BACKGROUND: Upon the discovery of ovarian cysts, obstetricians, gynecologists, and ultrasound examiners must address the common clinical challenge of distinguishing between benign and malignant ovarian tumors. Numerous types of ovarian tumors exist, ...

Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases.

Scientific reports
Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we investigated whether deep neural network (DNN) models can improve the accuracy of preoperative MRI-b...

T-SPOT with CT image analysis based on deep learning for early differential diagnosis of nontuberculous mycobacteria pulmonary disease and pulmonary tuberculosis.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
OBJECTIVES: This study aimed to establish a diagnostic algorithm combining T-SPOT with computed tomography image analysis based on deep learning (DL) for early differential diagnosis of nontuberculous mycobacteria pulmonary disease (NTM-PD) and pulmo...

Histologic Screening of Malignant Melanoma, Spitz, Dermal and Junctional Melanocytic Nevi Using a Deep Learning Model.

The American Journal of dermatopathology
OBJECTIVE: The integration of an artificial intelligence tool into pathologists' workflow may lead to a more accurate and timely diagnosis of melanocytic lesions, directly patient care. The objective of this study was to create and evaluate the perfo...

Deep learning to diagnose Hashimoto's thyroiditis from sonographic images.

Nature communications
Hashimoto's thyroiditis (HT) is the main cause of hypothyroidism. We develop a deep learning model called HTNet for diagnosis of HT by training on 106,513 thyroid ultrasound images from 17,934 patients and test its performance on 5051 patients from 2...

Artificial intelligence using deep learning analysis of endoscopic ultrasonography images for the differential diagnosis of pancreatic masses.

Endoscopy
BACKGROUND : There are several types of pancreatic mass, so it is important to distinguish between them before treatment. Artificial intelligence (AI) is a mathematical technique that automates learning and recognition of data patterns. This study ai...