AIMC Topic: Unnecessary Procedures

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Effective reduction of unnecessary biopsies through a deep-learning-assisted aggressive prostate cancer detector.

Scientific reports Apr 30, 2025
Despite being one of the most prevalent cancers, prostate cancer (PCa) shows a significantly high survival rate, provided there is timely detection and treatment. Currently, several screening and diagnostic tests are required to be carried out in ord...
Prostatic Neoplasms Prostate-Specific Antigen Neoplasm Grading Biopsy Unnecessary Procedures Multiparametric Magnetic Resonance Imaging Humans Male Deep Learning
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A Machine Learning Algorithm Avoids Unnecessary Paracentesis for Exclusion of SBP in Cirrhosis in Resource-limited Settings.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association Jun 19, 2024
BACKGROUND & AIMS: Despite the poor prognosis associated with missed or delayed spontaneous bacterial peritonitis (SBP) diagnosis, <15% get timely paracentesis, which persists despite guidelines/education in the United States. Measures to exclude SBP...
Liver Cirrhosis United States Bacterial Infections Paracentesis Unnecessary Procedures Retrospective Studies Female Humans Aged Machine Learning Male Algorithms Middle Aged Peritonitis Resource-Limited Settings
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Appropriate use of blood cultures in the emergency department through machine learning (ABC): study protocol for a randomised controlled non-inferiority trial.

BMJ open May 31, 2024
INTRODUCTION: The liberal use of blood cultures in emergency departments (EDs) leads to low yields and high numbers of false-positive results. False-positive, contaminated cultures are associated with prolonged hospital stays, increased antibiotic us...
Machine Learning Anti-Bacterial Agents Length of Stay Hospital Mortality Blood Culture Randomized Controlled Trials as Topic Humans Emergency Service, Hospital Netherlands Unnecessary Procedures Equivalence Trials as Topic
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Deep learning of mammogram images to reduce unnecessary breast biopsies: a preliminary study.

Breast cancer research : BCR May 24, 2024
BACKGROUND: Patients with a Breast Imaging Reporting and Data System (BI-RADS) 4 mammogram are currently recommended for biopsy. However, 70-80% of the biopsies are negative/benign. In this study, we developed a deep learning classification algorithm...
Retrospective Studies Middle Aged Carcinoma, Intraductal, Noninfiltrating Female Humans Deep Learning Unnecessary Procedures Aged Mammography Adult Biopsy Breast Neoplasms Breast
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Optimization of clinical risk-factor interpretation and radiological findings with machine learning for PIRADS category 3 patients.

The Prostate Nov 15, 2021
BACKGROUND: Due to the low cancer-detection rate in patients with PIRADS category 3 lesions, we created machine learning (ML) models to facilitate decision-making about whether to perform prostate biopsies or monitor clinical information without biop...
Magnetic Resonance Imaging Prostatic Neoplasms Prostate-Specific Antigen Ultrasonography, Interventional Prostate Research Design Aged Sensitivity and Specificity Male Risk Assessment Quality Improvement Image-Guided Biopsy Unnecessary Procedures Public Reporting of Healthcare Data Humans Machine Learning
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Comparison of British Thyroid Association, American College of Radiology TIRADS and Artificial Intelligence TIRADS with histological correlation: diagnostic performance for predicting thyroid malignancy and unnecessary fine needle aspiration rate.

The British journal of radiology Jun 9, 2021
OBJECTIVES: To compare diagnostic performance of British Thyroid Association (BTA), American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) and Artificial Intelligence TIRADS (AI-TIRADS) for thyroid nodule malignancy. To ...
Thyroidectomy Thyroid Neoplasms Ultrasonography Predictive Value of Tests Neoplasm Grading Practice Guidelines as Topic Biopsy, Fine-Needle Unnecessary Procedures Humans Adult Sensitivity and Specificity Male Middle Aged Adolescent Artificial Intelligence Retrospective Studies Female Aged Aged, 80 and over
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A Comparative Analysis of Two Machine Learning-Based Diagnostic Patterns with Thyroid Imaging Reporting and Data System for Thyroid Nodules: Diagnostic Performance and Unnecessary Biopsy Rate.

Thyroid : official journal of the American Thyroid Association Sep 9, 2020
The risk stratification system of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for thyroid nodules is affected by low diagnostic specificity. Machine learning (ML) methods can optimize the diagnostic perf...
Humans Machine Learning Adolescent Young Adult Retrospective Studies Adult Unnecessary Procedures Thyroid Neoplasms Clinical Decision-Making Male Elasticity Imaging Techniques Ultrasonography Female Middle Aged Tumor Burden Thyroid Nodule Reproducibility of Results China Image Interpretation, Computer-Assisted Predictive Value of Tests Aged Biopsy, Fine-Needle Aged, 80 and over
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Clinico-radiological characteristic-based machine learning in reducing unnecessary prostate biopsies of PI-RADS 3 lesions with dual validation.

European radiology Jun 10, 2020
OBJECTIVE: To evaluate machine learning-based classifiers in detecting clinically significant prostate cancer (PCa) with Prostate Imaging Reporting and Data System (PI-RADS) score 3 lesions.
Prostatic Neoplasms Prostate-Specific Antigen Prostate Validation Studies as Topic Image-Guided Biopsy Unnecessary Procedures Multiparametric Magnetic Resonance Imaging Logistic Models Support Vector Machine Decision Trees Area Under Curve Radiography Aged, 80 and over Male Middle Aged Ultrasonography ROC Curve Humans Retrospective Studies Machine Learning Reproducibility of Results Aged
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Artificial intelligence may help in predicting the need for additional surgery after endoscopic resection of T1 colorectal cancer.

Endoscopy Dec 22, 2017
BACKGROUND AND STUDY AIMS: Decisions concerning additional surgery after endoscopic resection of T1 colorectal cancer (CRC) are difficult because preoperative prediction of lymph node metastasis (LNM) is problematic. We investigated whether artificia...
Middle Aged Endoscopy Heuristics Risk Assessment Sensitivity and Specificity Japan Humans Models, Theoretical Colorectal Neoplasms Unnecessary Procedures Artificial Intelligence Lymphatic Metastasis Diagnostic Errors Prognosis Neoplasm Staging Male Female Aged
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High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision.

Radiology Oct 17, 2017
Purpose To develop a machine learning model that allows high-risk breast lesions (HRLs) diagnosed with image-guided needle biopsy that require surgical excision to be distinguished from HRLs that are at low risk for upgrade to cancer at surgery and t...
Young Adult Adult Breast Neoplasms Middle Aged Risk Assessment Unnecessary Procedures Follow-Up Studies Humans Prognosis Carcinoma, Intraductal, Noninfiltrating Machine Learning Clinical Decision-Making Watchful Waiting Female Precancerous Conditions Aged Image-Guided Biopsy Aged, 80 and over
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