AIMC Topic: Retrospective Studies
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American College of Surgeons survival calculator for biliary tract cancers: using machine learning to individualize predictions.
Surgery
Nov 26, 2024
BACKGROUND: Although cancer prognosis is most commonly estimated by tumor stage, survival is multifactorial. Our objective was to develop an American College of Surgeons "Biliary Tract Cancer Survival Calculator" prototype using machine learning to g...
A CT-based deep learning for segmenting tumors and predicting microsatellite instability in patients with colorectal cancers: a multicenter cohort study.
La Radiologia medica
Nov 26, 2024
PURPOSE: To develop and validate deep learning (DL) models using preoperative contrast-enhanced CT images for tumor auto-segmentation and microsatellite instability (MSI) prediction in colorectal cancer (CRC).
Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning.
Cardiovascular diabetology
Nov 26, 2024
BACKGROUND: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourab...
Atrial Fibrillation
Glycemic Control
Time Factors
Hospital Mortality
Predictive Value of Tests
Cause of Death
Female
Reproducibility of Results
Risk Factors
Aged
Aged, 80 and over
Male
Middle Aged
Risk Assessment
Blood Glucose
Biomarkers
Prognosis
Retrospective Studies
Critical Illness
Intensive Care Units
Humans
Machine Learning
Decision Support Techniques
Databases, Factual
Interpretable machine learning model based on CT semantic features and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors.
Scientific reports
Nov 26, 2024
To develop and validate a machine learning (ML) model which combined computed tomography (CT) semantic and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors (GISTs) patients. We retrospectively collected...
The Value of Whole-Volume Radiomics Machine Learning Model Based on Multiparametric MRI in Predicting Triple-Negative Breast Cancer.
Journal of computer assisted tomography
Nov 25, 2024
OBJECTIVE: This study aimed to investigate the value of radiomics analysis in the precise diagnosis of triple-negative breast cancer (TNBC) based on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coeffici...
The added value of including thyroid nodule features into large language models for automatic ACR TI-RADS classification based on ultrasound reports.
Japanese journal of radiology
Nov 25, 2024
OBJECTIVE: The ACR Thyroid Imaging, Reporting, and Data System (TI-RADS) uses a score based on ultrasound (US) imaging to stratify the risk of nodule malignancy and recommend appropriate follow-up. This study aims to analyze US reports and explore ho...
Effect of Artificial Intelligence as a Second Reader on the Lung Nodule Detection and Localization Accuracy of Radiologists and Non-radiology Physicians in Chest Radiographs: A Multicenter Reader Study.
Academic radiology
Nov 25, 2024
RATIONALE AND OBJECTIVES: Missed nodules in chest radiographs (CXRs) are common occurrences. We assessed the effect of artificial intelligence (AI) as a second reader on the accuracy of radiologists and non-radiology physicians in lung nodule detecti...
Aged
Sensitivity and Specificity
Male
Middle Aged
Lung Neoplasms
Solitary Pulmonary Nodule
Radiologists
Radiographic Image Interpretation, Computer-Assisted
Observer Variation
Artificial Intelligence
Retrospective Studies
Tomography, X-Ray Computed
Female
Reproducibility of Results
Humans
Radiography, Thoracic
A machine learning-based analysis of nationwide cancer comprehensive genomic profiling data across cancer types to identify features associated with recommendation of genome-matched therapy.
ESMO open
Nov 25, 2024
BACKGROUND: The low probability of identifying druggable mutations through comprehensive genomic profiling (CGP) and its financial and time costs hinder its widespread adoption. To enhance the effectiveness and efficiency of cancer precision medicine...
Time-dependent personalized prognostic analysis by machine learning in biochemical recurrence after radical prostatectomy: a retrospective cohort study.
BMC cancer
Nov 25, 2024
BACKGROUND: For biochemical recurrence following radical prostatectomy for prostate cancer, treatments such as radiation therapy and androgen deprivation therapy are administered. To diagnose postoperative recurrence as early as possible and to inter...
Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment.
Scientific reports
Nov 25, 2024
This bicenter retrospective analysis included 162 patients who had undergone prostate biopsy following prebiopsy MRI, excluding those with PCa identified only in the peripheral zone (PZ). DLR T2WI achieved a 69% reduction in scan time relative to TSE...
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