AIMC Topic: Treatment Failure
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Preoperatively predicting failure to achieve the minimum clinically important difference and the substantial clinical benefit in patient-reported outcome measures for total hip arthroplasty patients using machine learning.
BMC musculoskeletal disorders
Feb 14, 2025
BACKGROUND: Attention to the collection of patient-reported outcomes measures (PROMs) associated with total hip arthroplasty (THA) is growing. The aim of this study was to preoperatively predict failure to achieve the minimal clinically important dif...
Machine learning-based forecast of Helmet-CPAP therapy failure in Acute Respiratory Distress Syndrome patients.
Computer methods and programs in biomedicine
Dec 30, 2024
BACKGROUND AND OBJECTIVE: Helmet-Continuous Positive Airway Pressure (H-CPAP) is a non-invasive respiratory support that is used for the treatment of Acute Respiratory Distress Syndrome (ARDS), a severe medical condition diagnosed when symptoms like ...
Predictive accuracy of machine learning models for conservative treatment failure in thoracolumbar burst fractures.
BMC musculoskeletal disorders
Nov 18, 2024
BACKGROUND: The management of patients with thoracolumbar burst fractures remains a topic of debate, with conservative treatment being successful in most cases but not all. This study aimed to assess the utility of machine learning models (MLMs) in p...
Unsupervised Machine Learning to Identify Risk Factors of Pyeloplasty Failure in Ureteropelvic Junction Obstruction.
Journal of endourology
Sep 17, 2024
In adult patients with ureteropelvic junction obstruction (UPJO), little data exist on predicting pyeloplasty outcome, and there is no unified definition of pyeloplasty success. As such, defining pyeloplasty success retrospectively is particularly v...
A transparent machine learning algorithm uncovers HbA1c patterns associated with therapeutic inertia in patients with type 2 diabetes and failure of metformin monotherapy.
International journal of medical informatics
Jul 15, 2024
AIMS: This study aimed to identify and categorize the determinants influencing the intensification of therapy in Type 2 Diabetes (T2D) patients with suboptimal blood glucose control despite metformin monotherapy.
Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia.
BMC pulmonary medicine
Jul 1, 2024
AIM: To develop a decision-support tool for predicting extubation failure (EF) in neonates with bronchopulmonary dysplasia (BPD) using a set of machine-learning algorithms.
Prediction of the treatment response and local failure of patients with brain metastasis treated with stereotactic radiosurgery using machine learning: A systematic review and meta-analysis.
Neurosurgical review
Apr 30, 2024
BACKGROUND: Stereotactic radiosurgery (SRS) effectively treats brain metastases. It can provide local control, symptom relief, and improved survival rates, but it poses challenges in selecting optimal candidates, determining dose and fractionation, m...
Deep Learning-Guided Dosimetry for Mitigating Local Failure of Patients With Non-Small Cell Lung Cancer Receiving Stereotactic Body Radiation Therapy.
International journal of radiation oncology, biology, physics
Dec 5, 2023
PURPOSE: Non-small cell lung cancer (NSCLC) stereotactic body radiation therapy with 50 Gy/5 fractions is sometimes considered controversial, as the nominal biologically effective dose (BED) of 100 Gy is felt by some to be insufficient for long-term ...
Predicting Substance Use Treatment Failure with Transfer Learning.
Substance use & misuse
Sep 21, 2022
Transfer learning, which involves repurposing a trained model on a related task, may allow for better predictions with substance use data than models that are trained using the target data alone. This approach may also be useful for small clinical da...
Multimodal deep learning model on interim [F]FDG PET/CT for predicting primary treatment failure in diffuse large B-cell lymphoma.
European radiology
Aug 27, 2022
OBJECTIVES: The prediction of primary treatment failure (PTF) is necessary for patients with diffuse large B-cell lymphoma (DLBCL) since it serves as a prominent means for improving front-line outcomes. Using interim F-fluoro-2-deoxyglucose ([F]FDG) ...
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