AIMC Topic: Retrospective Studies

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Machine learning based peri-surgical risk calculator for abdominal related emergency general surgery: a multicenter retrospective study.

International journal of surgery (London, England) Jun 1, 2024
BACKGROUND: Currently, there is a lack of ideal risk prediction tools in the field of emergency general surgery (EGS). The American Association for the Surgery of Trauma recommends developing risk assessment tools specifically for EGS-related disease...
Aged Adult Male Middle Aged Humans Machine Learning Retrospective Studies Female Abdomen General Surgery Surgical Procedures, Operative APACHE Acute Care Surgery Risk Assessment Postoperative Complications Emergencies China
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Surgical factors play a critical role in predicting functional outcomes using machine learning in robotic-assisted total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA May 31, 2024
PURPOSE: Predictive models help determine predictive factors necessary to improve functional outcomes after total knee arthroplasty (TKA). However, no study has assessed predictive models for functional outcomes after TKA based on the new concepts of...
Retrospective Studies Middle Aged Arthroplasty, Replacement, Knee Female Treatment Outcome Patient Reported Outcome Measures Aged Recovery of Function Humans Osteoarthritis, Knee Male Robotic Surgical Procedures Minimal Clinically Important Difference Machine Learning
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Construction of the prediction model for multiple myeloma based on machine learning.

International journal of laboratory hematology May 31, 2024
INTRODUCTION: The global burden of multiple myeloma (MM) is increasing every year. Here, we have developed machine learning models to provide a reference for the early detection of MM.
Middle Aged Female Humans ROC Curve Aged Machine Learning Support Vector Machine Adult Retrospective Studies Multiple Myeloma Male
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Deep Learning-Based Segmentation and Risk Stratification for Gastrointestinal Stromal Tumors in Transabdominal Ultrasound Imaging.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine May 31, 2024
PURPOSE: To develop a deep neural network system for the automatic segmentation and risk stratification prediction of gastrointestinal stromal tumors (GISTs).
Gastrointestinal Neoplasms Gastrointestinal Stromal Tumors Risk Assessment Deep Learning Ultrasonography Abdomen Female Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Male Middle Aged Humans Prospective Studies Retrospective Studies
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No code machine learning: validating the approach on use-case for classifying clavicle fractures.

Clinical imaging May 31, 2024
PURPOSE: We created an infrastructure for no code machine learning (NML) platform for non-programming physicians to create NML model. We tested the platform by creating an NML model for classifying radiographs for the presence and absence of clavicle...
Fractures, Bone Adult Humans Radiography Sensitivity and Specificity Machine Learning Clavicle Male Retrospective Studies Middle Aged Female
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Development and Validation of a Machine Learning Model for Bone Metastasis in Prostate Cancer: Based on Inflammatory and Nutritional Indicators.

Urology May 31, 2024
OBJECTIVE: To establish a predictive model for prostate cancer bone metastasis utilizing multiple machine learning algorithms.
Humans Middle Aged Bone Neoplasms Machine Learning Decision Trees Retrospective Studies Aged Prostatic Neoplasms Male
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Predicting treatment resistance in schizophrenia patients: Machine learning highlights the role of early pathophysiologic features.

Schizophrenia research May 31, 2024
Detecting patients with a high-risk profile for treatment-resistant schizophrenia (TRS) can be beneficial for implementing individually adapted therapeutic strategies and better understanding the TRS etiology. The aim of this study was to explore, wi...
Young Adult Adult Male Middle Aged Adolescent Medication Adherence Schizophrenia Schizophrenia, Treatment-Resistant Prognosis Retrospective Studies Female Risk Factors Humans Machine Learning Antipsychotic Agents
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Deep learning-based magnetic resonance imaging analysis for chronic cerebral hypoperfusion risk.

Medical physics May 31, 2024
BACKGROUND: Chronic cerebral hypoperfusion (CCH) is a frequently encountered clinical condition that poses a diagnostic challenge due to its nonspecific symptoms.
Humans Retrospective Studies Middle Aged Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Chronic Disease Female Aged Adult Male Cerebrovascular Disorders Cerebrovascular Circulation
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Predicting Chronic Pain and Treatment Outcomes Using Machine Learning Models Based on High-dimensional Clinical Data From a Large Retrospective Cohort.

Clinical therapeutics May 31, 2024
PURPOSE: To identify factors and indicators that affect chronic pain and pain relief, and to develop predictive models using machine learning.
Pain Management Chronic Pain Humans Machine Learning Retrospective Studies Female Middle Aged Logistic Models Treatment Outcome Risk Factors Decision Trees Aged Adult Male
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Deep learning-based automatic measurement system for patellar height: a multicenter retrospective study.

Journal of orthopaedic surgery and research May 31, 2024
BACKGROUND: The patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patell...
Patella Middle Aged Deep Learning Radiography Female Humans Automation Adult Retrospective Studies Male
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