output
20212026
most citedKMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation

119 citations

5 papers

cs.LG2026

Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health

Donna Tjandra, Trenton Chang, Sonali Parbhoo +8

Objective: The growing availability of large-scale observational clinical datasets and challenges in conducting randomized controlled trials have spurred enthusiasm in using causal…

q-bio.NC2025119 cited

KMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation

L Cif, D Demailly, JP Lin +112

Heterozygous mutations in KMT2B are associated with an early-onset, progressive, and often complex dystonia (DYT28). Key characteristics of typical disease include focal motor feat…

cs.HC202478 cited

Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for Radiology

Nur Yildirim, Hannah Richardson, Maria T. Wetscherek +18

Recent advances in AI combine large language models (LLMs) with vision encoders that bring forward unprecedented technical capabilities to leverage for a wide range of healthcare a…

cs.CV2021

Transductive image segmentation: Self-training and effect of uncertainty estimation

Konstantinos Kamnitsas, Stefan Winzeck, Evgenios N. Kornaropoulos +9

Semi-supervised learning (SSL) uses unlabeled data during training to learn better models. Previous studies on SSL for medical image segmentation focused mostly on improving model…

q-bio.QM20212 cited

Machine Learning and Glioblastoma: Treatment Response Monitoring Biomarkers in 2021

Thomas Booth, Bernice Akpinar, Andrei Roman +10

The aim of the systematic review was to assess recently published studies on diagnostic test accuracy of glioblastoma treatment response monitoring biomarkers in adults, developed…