AIMC Topic: Treatment Outcome

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The role of artificial intelligence in predicting the clinical outcomes associated with different therapeutic approaches for vestibular schwannoma: A systematic review and meta-analysis.

Neurosurgical review
INTRODUCTION: Vestibular schwannoma is the most common neoplasm located at the skull base. The therapeutic strategy for managing vestibular schwannoma is formulated based on individual patient characteristics and specific imaging findings. Recently, ...

Applications of machine learning in deep brain stimulation for major depressive disorder: a systematic review and meta-analysis.

Neurosurgical review
Depression is a significant public health issue, consistently ranking among the leading causes of mortality, reduced quality of life, and economic burden. Despite available treatments, approximately one-third of patients exhibit resistance to standar...

Safety and efficacy of add-on robotic therapy for early mobilization in intermediate neurocritical care: a pilot study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Early mobilization has become a cornerstone of critical care due to its benefits in mitigating adverse effects associated with prolonged immobility. Individuals with critical neurosurgical conditions face unique challenges for mobilizatio...

Robotic adrenalectomy: a comprehensive review of perioperative outcomes, comparative efficacy, and technological advancements.

Journal of robotic surgery
The adrenal glands are small but vital endocrine organs responsible for hormone production, which is essential for stress response, fluid balance, and blood pressure regulation. Adrenalectomy, the surgical removal of one or both adrenal glands, is in...

Effects of robot assisted mirror therapy on motor function and cortical activation in patients with right hemisphere damage.

Scientific reports
Robot-assisted mirror therapy (MRT) is a cutting-edge rehabilitative treatment that combines mirror therapy and rehabilitation robots and can improve stroke patient participation in rehabilitation training. The aim of this study was to investigate th...

Machine learning for endoscopic third ventriculostomy success prediction-a systematic review and meta-analysis.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
BACKGROUND: Endoscopic third ventriculostomy (ETV) is a common treatment for pediatric obstructive hydrocephalus, but predicting its success remains challenging. Traditional predictive tools, such as the Endoscopic Third Ventriculostomy Success Score...

Development and validation of machine-learning model based on dynamic tumor markers in predicting pathological complete response after neoadjuvant chemoradiotherapy in patients with locally advanced rectal cancer: a multicenter cohort study.

International journal of colorectal disease
OBJECTIVE: In this study, we constructed a new pCR predictor based on dynamic tumor marker changes before and after NCRT, the dynamic tumor marker score (DTMS), and combined it with other clinicopathological features to build a machine-learning model...

Machine learning-based prediction of post-operative outcomes in robotic-assisted radical prostatectomy: a multi-variable analysis of 758 cases.

Journal of robotic surgery
Robotic-assisted radical prostatectomy (RARP) has become the gold standard treatment for localized prostate cancer. However, predicting post-operative outcomes remains challenging. This study aims to develop and validate predictive models for key out...

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry.

Scientific reports
To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monitoring. Real-world da...