AIMC Topic: Treatment Outcome
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Advantages and effectiveness of AI three-dimensional reconstruction technology in the preoperative planning of total hip arthroplasty.
Scientific reports
Jul 9, 2025
In order to explore the application effect of artificial intelligence (AI) 3D reconstruction technology in total hip arthroplasty (THA), this study included a total of 109 patients with unilateral femoral head ischemic necrosis. According to the preo...
Integrative multimodal ultrasound and radiomics for early prediction of neoadjuvant therapy response in breast cancer: a clinical study.
BMC cancer
Jul 9, 2025
PURPOSE: This study aimed to develop an early predictive model for neoadjuvant therapy (NAT) response in breast cancer by integrating multimodal ultrasound (conventional B-mode, shear-wave elastography, and contrast-enhanced ultrasound) and radiomics...
Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn's disease.
Annals of medicine
Jul 5, 2025
BACKGROUND: Crohn's disease (CD) is a chronic inflammatory bowel disease, with infliximab (IFX) commonly used for treatment. However, no clinically applicable model currently exists to predict the response of patients with CD to IFX therapy. Given th...
Effects of device-assisted practice of activities of daily living in a close-to-normal pattern on upper extremity motor recovery in individuals with moderate to severe stroke: study protocol of a randomized control trial.
Trials
Jul 4, 2025
BACKGROUND: The majority of individuals with chronic stroke have residual upper extremity (UE) disability which they cite as their greatest barrier to recovery. Using orthoses, robotic devices, and functional electrical stimulation (FES) represent re...
Humans
Robotics
Disability Evaluation
Double-Blind Method
Equipment Design
Stroke
Research Design
Severity of Illness Index
Time Factors
Treatment Outcome
Recovery of Function
Upper Extremity
Electric Stimulation Therapy
Activities of Daily Living
Stroke Rehabilitation
Orthotic Devices
Clinical Protocols
Paresis
Motor Activity
Predicting ESWL success for ureteral stones: a radiomics-based machine learning approach.
BMC medical imaging
Jul 4, 2025
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model that integrates radiomics and conventional radiological features to predict the success of single-session extracorporeal shock wave lithotripsy (ESWL) for ureteral sto...
A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs.
Scientific reports
Jul 4, 2025
Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are co...
Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.
Science advances
Jul 4, 2025
Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor samples from 149 Chinese patients with breast cancer across ERHER2, ERHER2, and ERHER2 subtypes, cat...
Deep molecular profiling of synovial biopsies in the STRAP trial identifies signatures predictive of treatment response to biologic therapies in rheumatoid arthritis.
Nature communications
Jul 2, 2025
Approximately 40% of patients with rheumatoid arthritis do not respond to individual biologic therapies, while biomarkers predictive of treatment response are lacking. Here we analyse RNA-sequencing (RNA-Seq) of pre-treatment synovial tissue from the...
The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms.
Scientific reports
Jul 2, 2025
Hematoporphyrin monomethyl ether-photodynamic therapy (HMME-PDT) is a safe and effective treatment for port-wine stain (PWS). Comprehensive methods for predicting HMME-PDT efficacy based on clinical factors are lacking. This study aims to develop and...
Preoperative prediction of major adverse outcomes after total arch replacement in acute type A aortic dissection based on machine learning ensemble.
Scientific reports
Jul 1, 2025
A machine learning model was developed and validated to predict postoperative complications in patients with acute type A aortic dissection (ATAAD) who underwent total arch replacement combined with frozen elephant trunk (TAR + FET), with the goal of...
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