AIMC Topic: ROC Curve

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Performance of deep learning for detection of chronic kidney disease from retinal fundus photographs: A systematic review and meta-analysis.

European journal of ophthalmology
OBJECTIVE: Deep learning has been used to detect chronic kidney disease (CKD) from retinal fundus photographs. We aim to evaluate the performance of deep learning for CKD detection.

Distilling Knowledge From an Ensemble of Vision Transformers for Improved Classification of Breast Ultrasound.

Academic radiology
RATIONALE AND OBJECTIVES: To develop a deep learning model for the automated classification of breast ultrasound images as benign or malignant. More specifically, the application of vision transformers, ensemble learning, and knowledge distillation i...

Detecting Adverse Pathology of Prostate Cancer With a Deep Learning Approach Based on a 3D Swin-Transformer Model and Biparametric MRI: A Multicenter Retrospective Study.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Accurately detecting adverse pathology (AP) presence in prostate cancer patients is important for personalized clinical decision-making. Radiologists' assessment based on clinical characteristics showed poor performance for detecting AP p...

The auxiliary diagnosis of thyroid echogenic foci based on a deep learning segmentation model: A two-center study.

European journal of radiology
OBJECTIVE: The aim of this study is to develop AI-assisted software incorporating a deep learning (DL) model based on static ultrasound images. The software aims to aid physicians in distinguishing between malignant and benign thyroid nodules with ec...

Detection of the pathological exposure of pulp using an artificial intelligence tool: a multicentric study over periapical radiographs.

BMC oral health
BACKGROUND: Introducing artificial intelligence (AI) into the medical field proved beneficial in automating tasks and streamlining the practitioners' lives. Hence, this study was conducted to design and evaluate an AI tool called Make Sure Caries Det...

The accuracy of artificial intelligence in predicting COVID-19 patient mortality: a systematic review and meta-analysis.

BMC medical informatics and decision making
BACKGROUND: The purpose of this paper was to systematically evaluate the application value of artificial intelligence in predicting mortality among COVID-19 patients.

The accuracy of artificial intelligence used for non-melanoma skin cancer diagnoses: a meta-analysis.

BMC medical informatics and decision making
BACKGROUND: With rising incidence of skin cancer and relatively increased mortality rates, an improved diagnosis of such a potentially fatal disease is of vital importance. Although frequently curable, it nevertheless places a considerable burden upo...

Deep Learning for Localized Detection of Optic Disc Hemorrhages.

American journal of ophthalmology
PURPOSE: To develop an automated deep learning system for detecting the presence and location of disc hemorrhages in optic disc photographs.

Prediction of gestational diabetes mellitus at the first trimester: machine-learning algorithms.

Archives of gynecology and obstetrics
PURPOSE: Short- and long-term complications of gestational diabetes mellitus (GDM) involving pregnancies and offspring warrant the development of an effective individualized risk prediction model to reduce and prevent GDM together with its associated...

Development of a deep learning-based model to diagnose mixed-type gastric cancer accurately.

The international journal of biochemistry & cell biology
OBJECTIVE: The accurate diagnosis of mixed-type gastric cancer from pathology images presents a formidable challenge for pathologists, given its intricate features and resemblance to other subtypes of gastric cancer. Artificial Intelligence has the p...