AIMC Topic: Treatment Outcome
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Predicting treatment response to cognitive behavior therapy in social anxiety disorder on the basis of demographics, psychiatric history, and scales: A machine learning approach.
PloS one
Mar 18, 2025
Only about half of patients with social anxiety disorder (SAD) respond substantially to cognitive behavioral therapy (CBT). However, there has been little evidence available to clinicians or patients about whether any individual patient is more or le...
A clinical data-driven machine learning approach for predicting the effectiveness of piperacillin-tazobactam in treating lower respiratory tract infections.
BMC pulmonary medicine
Mar 17, 2025
BACKGROUND: In hospitalized patients, inadequate antibiotic dosage leading to bacterial resistance and increased antimicrobial use intensity due to overexposure to antibiotics are common problems. In the present study, we constructed a machine learni...
Histopathology based AI model predicts anti-angiogenic therapy response in renal cancer clinical trial.
Nature communications
Mar 17, 2025
Anti-angiogenic (AA) therapy is a cornerstone of metastatic clear cell renal cell carcinoma (ccRCC) treatment, but not everyone responds, and predictive biomarkers are lacking. CD31, a marker of vasculature, is insufficient, and the Angioscore, an RN...
State-of-the-art for automated machine learning predicts outcomes in poor-grade aneurysmal subarachnoid hemorrhage using routinely measured laboratory & radiological parameters: coagulation parameters and liver function as key prognosticators.
Neurosurgical review
Mar 17, 2025
The objective of this study was to develop and evaluate automated machine learning (aML) models for predicting short-term (1-month) and medium-term (3-month) functional outcomes [Modified Rankin Scale (mRS)] in patients suffering from poor-grade aneu...
Automated Identification of Stroke Thrombolysis Contraindications from Synthetic Clinical Notes: A Proof-of-Concept Study.
Cerebrovascular diseases extra
Mar 17, 2025
INTRODUCTION: Timely thrombolytic therapy improves outcomes in acute ischemic stroke. Manual chart review to screen for thrombolysis contraindications may be time-consuming and prone to errors. We developed and tested a large language model (LLM)-bas...
Predicting orthognathic surgery results as postoperative lateral cephalograms using graph neural networks and diffusion models.
Nature communications
Mar 16, 2025
Orthognathic surgery, or corrective jaw surgery, is performed to correct severe dentofacial deformities and is increasingly sought for cosmetic purposes. Accurate prediction of surgical outcomes is essential for selecting the optimal treatment plan a...
Voxel-level radiomics and deep learning for predicting pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant immunotherapy and chemotherapy.
Journal for immunotherapy of cancer
Mar 15, 2025
BACKGROUND: Accurate prediction of pathologic complete response (pCR) following neoadjuvant immunotherapy combined with chemotherapy (nICT) is crucial for tailoring patient care in esophageal squamous cell carcinoma (ESCC). This study aimed to develo...
Use machine learning to predict treatment outcome of early childhood caries.
BMC oral health
Mar 15, 2025
BACKGROUND: Early childhood caries (ECC) is a major oral health problem among preschool children that can significantly influence children's quality of life. Machine learning can accurately predict the treatment outcome but its use in ECC management ...
Establishing a Deep Learning Model That Integrates Pretreatment and Midtreatment Computed Tomography to Predict Treatment Response in Non-Small Cell Lung Cancer.
International journal of radiation oncology, biology, physics
Mar 13, 2025
PURPOSE: Patients with identical stages or similar tumor volumes can vary significantly in their responses to radiation therapy (RT) due to individual characteristics, making personalized RT for non-small cell lung cancer (NSCLC) challenging. This st...
Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Methods.
Tomography (Ann Arbor, Mich.)
Mar 13, 2025
RATIONALE: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response of NAC for patients with LABC before initiating treatment would be valuable to customize therapies and ensure t...
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