AIMC Topic: Treatment Outcome

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Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.

BMC cardiovascular disorders Dec 20, 2024
INTRODUCTION: Congenital heart disease (CHD) represents the most common group of congenital anomalies, constitutes a significant contributor to the burden of non-communicable diseases, highlighting the critical need for improved risk assessment tools...
Decision Support Techniques Female Infant, Newborn Risk Factors Young Adult Adult Male Risk Assessment Predictive Value of Tests Postoperative Complications Cardiac Surgical Procedures Infant Adolescent Heart Defects, Congenital Time Factors Child, Preschool Child Humans Treatment Outcome Artificial Intelligence
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Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.

BMC cardiovascular disorders Dec 19, 2024
BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rates remain variable. Predicting the success of catheter ablation is crucial for patient selection and management. This research seeks to create a machi...
Iran Atrial Fibrillation Catheter Ablation Recurrence Treatment Outcome Longitudinal Studies Predictive Value of Tests Registries Decision Support Techniques Prospective Studies Female Risk Factors Aged Adult Male Middle Aged Risk Assessment Time Factors Humans Machine Learning
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Textbook outcome in liver surgery for intrahepatic cholangiocarcinoma: defining predictors of an optimal postoperative course using machine learning.

HPB : the official journal of the International Hepato Pancreato Biliary Association Dec 18, 2024
BACKGROUND: We sought to define textbook outcome in liver surgery (TOLS) for intrahepatic cholangiocarcinoma (ICC) by considering the implications of perioperative outcomes on overall survival (OS).
Hepatectomy Bile Duct Neoplasms Cholangiocarcinoma Male Middle Aged Time Factors Treatment Outcome Databases, Factual Retrospective Studies Female Risk Factors Aged Humans Machine Learning
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Machine learning for predicting post-operative outcomes in meningiomas: a systematic review and meta-analysis.

Acta neurochirurgica Dec 17, 2024
PURPOSE: Meningiomas are the most common primary brain tumour and account for over one-third of cases. Traditionally, estimations of morbidity and mortality following surgical resection have depended on subjective assessments of various factors, incl...
Machine Learning Treatment Outcome Meningioma Meningeal Neoplasms Humans
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Artificial intelligence-assisted fitting method using corneal topography outcomes enhances success rate in orthokeratology lens fitting.

Contact lens & anterior eye : the journal of the British Contact Lens Association Dec 16, 2024
PURPOSE: Based on ideal outcomes of corneal topography following orthokeratology (OK), an innovative machine learning algorithm for corneal refractive therapy (CRT) was developed to investigate the precision of artificial intelligence (AI)-assisted O...
Reproducibility of Results Young Adult Adult Male Middle Aged Visual Acuity Refraction, Ocular Corneal Topography Humans Myopia Contact Lenses Artificial Intelligence Adolescent Prosthesis Fitting Algorithms Child Orthokeratologic Procedures Retrospective Studies Treatment Outcome Female
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A clinical practical model for preoperative prediction of visual outcome for pituitary adenoma patients in a retrospective and prospective study.

Frontiers in endocrinology Dec 13, 2024
OBJECTIVE: Preoperative prediction of visual recovery after pituitary adenoma resection surgery remains challenging. This study aimed to investigate the value of clinical and radiological features in preoperatively predicting visual outcomes after su...
Middle Aged Treatment Outcome Magnetic Resonance Imaging Pituitary Neoplasms Adenoma Female Visual Acuity Humans Aged Prospective Studies Vision Disorders Young Adult Prognosis Recovery of Function Adult Retrospective Studies Male
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Does machine learning improve prediction accuracy of the Endoscopic Third Ventriculostomy Success Score? A contemporary Hydrocephalus Clinical Research Network cohort study.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery Dec 10, 2024
PURPOSE: This Hydrocephalus Clinical Research Network (HCRN) study had two aims: (1) to compare the predictive performance of the original ETV Success Score (ETVSS) using logistic regression modeling with other newer machine learning models and (2) t...
Humans Machine Learning Female Third Ventricle Child Male Treatment Outcome Infant Hydrocephalus Cohort Studies Ventriculostomy Child, Preschool Neuroendoscopy
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Model-informed approach to estimate treatment effect in placebo-controlled clinical trials using an artificial intelligence-based propensity weighting methodology to account for non-specific responses to treatment.

Journal of pharmacokinetics and pharmacodynamics Dec 10, 2024
In randomized, placebo controlled clinical trials (RCT) in major depressive disorders (MDD), treatment response (TR) is estimated by the change from baseline at study-end (EOS) of the scores of clinical scales used for assessing disease severity. Tre...
Humans Artificial Intelligence Depressive Disorder, Major Treatment Outcome Models, Statistical Randomized Controlled Trials as Topic Propensity Score Antidepressive Agents Placebo Effect
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Prevalence of fungal colonization among patients with psoriasis in difficult-to-treat areas: impact of apremilast on mycotic burden and clinical outcomes.

Frontiers in immunology Dec 10, 2024
INTRODUCTION: Fungi, including , may be a trigger or exacerbate psoriasis, especially in difficult to treat (DTT) areas, through the activation of IL-17/23 axis.
Middle Aged Prevalence Treatment Outcome Psoriasis Candida Female Aged Adult Male Thalidomide Humans Candidiasis Cytokines Anti-Inflammatory Agents, Non-Steroidal
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Utility of a Large Language Model for Extraction of Clinical Findings from Healthcare Data following Lung Ablation: A Feasibility Study.

Journal of vascular and interventional radiology : JVIR Dec 9, 2024
To assess the feasibility of utilizing a large language model (LLM) in extracting clinically relevant information from healthcare data in patients who have undergone microwave ablation for lung tumors. In this single-center retrospective study, radio...
Predictive Value of Tests Natural Language Processing Feasibility Studies Neoplasm Recurrence, Local Data Mining Male Middle Aged Time Factors Lung Neoplasms Treatment Outcome Pneumothorax Hemoptysis Microwaves Recurrence Large Language Models Hemothorax Ablation Techniques Humans Retrospective Studies Electronic Health Records Female Reproducibility of Results Aged
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