AIMC Topic: Retrospective Studies

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Multimodal deep learning fusion of ultrafast-DCE MRI and clinical information for breast lesion classification.

Computers in biology and medicine Feb 19, 2025
BACKGROUND: Breast cancer is the most common cancer worldwide, and magnetic resonance imaging (MRI) constitutes a very sensitive technique for invasive cancer detection. When reviewing breast MRI examination, clinical radiologists rely on multimodal ...
Contrast Media Adult Humans Breast Neoplasms Magnetic Resonance Imaging Middle Aged Breast Retrospective Studies Deep Learning Image Interpretation, Computer-Assisted Female Aged
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Diagnosis of Acute Appendicitis with Machine Learning-Based Computer Tomography: Diagnostic Reliability and Role in Clinical Management.

Journal of laparoendoscopic & advanced surgical techniques. Part A Feb 19, 2025
Acute appendicitis (AA) is a common surgical emergency affecting 7-8% of the population. Timely diagnosis and treatment are crucial for preventing serious morbidity and mortality. Diagnosis typically involves physical examination, laboratory tests, ...
Child Acute Disease Appendicitis Adult Male Middle Aged Adolescent Retrospective Studies Tomography, X-Ray Computed Female Humans Reproducibility of Results Machine Learning Young Adult
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Artificial Intelligence ECG Diastolic Dysfunction and Survival in Cardiac Intensive Care Unit Patients.

Journal of the American Heart Association Feb 19, 2025
BACKGROUND: Left ventricular diastolic dysfunction (LVDD) predicts mortality in patients in cardiac intensive care units. An artificial intelligence enhanced ECG (AIECG) algorithm can predict LVDD and mortality in general populations but has not been...
Middle Aged Coronary Care Units Humans Aged Hospital Mortality Diastole Male Artificial Intelligence Electrocardiography Ventricular Function, Left Retrospective Studies Echocardiography Ventricular Dysfunction, Left Female
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Impact of Sepsis Onset Timing on All-Cause Mortality in Acute Pancreatitis: A Multicenter Retrospective Cohort Study.

Journal of intensive care medicine Feb 18, 2025
BackgroundSepsis complicates acute pancreatitis (AP), increasing mortality risk. Few studies have examined how sepsis and its onset timing affect mortality in AP. This study evaluates the association between sepsis occurrence and all-cause mortality ...
Propensity Score Kaplan-Meier Estimate Pancreatitis Risk Factors Aged Adult Male Time Factors Hospital Mortality Middle Aged Acute Disease Humans Sepsis Retrospective Studies Intensive Care Units Female
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Automated quantification of brain PET in PET/CT using deep learning-based CT-to-MR translation: a feasibility study.

European journal of nuclear medicine and molecular imaging Feb 18, 2025
PURPOSE: Quantitative analysis of PET images in brain PET/CT relies on MRI-derived regions of interest (ROIs). However, the pairs of PET/CT and MR images are not always available, and their alignment is challenging if their acquisition times differ c...
Brain Retrospective Studies Female Aged Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Positron Emission Tomography Computed Tomography Feasibility Studies Automation Adult Male Middle Aged Deep Learning
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Dose prediction via deep learning to enhance treatment planning of lung radiotherapy including simultaneous integrated boost techniques.

Medical physics Feb 18, 2025
BACKGROUND: Recent studies have shown deep learning techniques are able to predict three-dimensional (3D) dose distributions of radiotherapy treatment plans. However, their use in dose prediction for treatments with varied prescription doses includin...
Retrospective Studies Deep Learning Lung Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiation Dosage Radiotherapy Dosage Radiotherapy, Intensity-Modulated Humans
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Interpretation of basal nuclei in brain dopamine transporter scans using a deep convolutional neural network.

Nuclear medicine communications Feb 18, 2025
OBJECTIVE: Functional imaging using the dopamine transporter (DAT) as a biomarker has proven effective in assessing dopaminergic neuron degeneration in the striatum. In assessing the neuron degeneration, visual and semiquantitative methods are used t...
Humans Neural Networks, Computer Male Middle Aged Deep Learning Convolutional Neural Networks Image Processing, Computer-Assisted Brain Retrospective Studies Female Aged Parkinson Disease Image Interpretation, Computer-Assisted Tomography, Emission-Computed, Single-Photon Dopamine Plasma Membrane Transport Proteins
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Predicting malignant risk of ground-glass nodules using convolutional neural networks based on dual-time-point F-FDG PET/CT.

Cancer imaging : the official publication of the International Cancer Imaging Society Feb 18, 2025
BACKGROUND: Accurately predicting the malignant risk of ground-glass nodules (GGOs) is crucial for precise treatment planning. This study aims to utilize convolutional neural networks based on dual-time-point F-FDG PET/CT to predict the malignant ris...
Convolutional Neural Networks Lung Neoplasms Solitary Pulmonary Nodule Positron Emission Tomography Computed Tomography Radiopharmaceuticals Aged Humans Fluorodeoxyglucose F18 Adult Neural Networks, Computer Male Retrospective Studies Middle Aged Female
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Deep learning-based automated guide for defining a standard imaging plane for developmental dysplasia of the hip screening using ultrasonography: a retrospective imaging analysis.

BMC medical informatics and decision making Feb 18, 2025
BACKGROUND: We aimed to propose a deep-learning neural network model for automatically detecting five landmarks during a two-dimensional (2D) ultrasonography (US) scan to develop a standard plane for developmental dysplasia of the hip (DDH) screening...
Ultrasonography Anatomic Landmarks Developmental Dysplasia of the Hip Female Male Humans Infant Neural Networks, Computer Deep Learning Retrospective Studies
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Integrating ultrasound radiomics and clinicopathological features for machine learning-based survival prediction in patients with nonmetastatic triple-negative breast cancer.

BMC cancer Feb 18, 2025
OBJECTIVE: This study aimed to evaluate the predictive value of implementing machine learning models based on ultrasound radiomics and clinicopathological features in the survival analysis of triple-negative breast cancer (TNBC) patients.
Triple Negative Breast Neoplasms Ultrasonography, Mammary Middle Aged Ultrasonography ROC Curve Nomograms Machine Learning Prospective Studies Prognosis Retrospective Studies Female Aged Adult Radiomics Humans
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