Variation in prognosis and treatment outcome in juvenile myoclonic epilepsy: a Biology of Juvenile Myoclonic Epilepsy Consortium proposal for a practical definition …
Reliable definitions, classifications and prognostic models are the cornerstones of stratified
medicine, but none of the current classifications systems in epilepsy address prognostic or …
medicine, but none of the current classifications systems in epilepsy address prognostic or …
Proposing causal sequence of death by neural machine translation in public health informatics
Each year there are nearly 57 million deaths worldwide, with over 2.7 million in the United
States. Timely, accurate and complete death reporting is critical for public health, especially …
States. Timely, accurate and complete death reporting is critical for public health, especially …
Mitigating patient-to-patient variation in EEG seizure detection using meta transfer learning
Electroencephalogram (EEG) signals can be used for seizure detection, but the seizure
patterns found in between patient's EEGs can have significant variations. Specifically, focal …
patterns found in between patient's EEGs can have significant variations. Specifically, focal …
[HTML][HTML] Comparing the efficacy of anti-seizure medications using matched cohorts on a large insurance claims database
Epilepsy is a severe chronic neurological disease affecting 60 million people worldwide.
Primary treatment is with anti-seizure medicines (ASMs), but many patients continue to …
Primary treatment is with anti-seizure medicines (ASMs), but many patients continue to …
Regularization of deep neural networks for EEG seizure detection to mitigate overfitting
Seizure detection is a major goal for simplifying the workflow of clinicians working on EEG
records. Current algorithms can only detect seizures effectively for patients already …
records. Current algorithms can only detect seizures effectively for patients already …
Automated Seizure Detection using Transformer Models on Multi-Channel EEGs
Epilepsy is a prevalent neurological disorder characterized by recurring seizures, affecting
approximately 50 million individuals globally. Given the potential severity of the associated …
approximately 50 million individuals globally. Given the potential severity of the associated …
Automating Treatment Recommendations for Children with Cerebral Palsy Based on Multi-Modal Clinical Data
Physical disability of children caused by Cerebral Palsy has a prevalence of 2.5 per 1000
births and disrupts body movements such as gait that is essential for healthy pediatric …
births and disrupts body movements such as gait that is essential for healthy pediatric …
An information theoretic learning for causal direction identification
Causal inference has been one of the central problems in many data science research and
one of the most important problem in causal inference is to draw causal conclusions using …
one of the most important problem in causal inference is to draw causal conclusions using …
Feature Selection Based on Causal Analysis Algorithm for Speech Emotion Recognition
P Du, KX Wang, H Cui, XD Liu - 2023 16th International …, 2023 - ieeexplore.ieee.org
Feature selection is an important step of pre-processing in machine learning and data
analysis. However, existing feature selection algorithms rarely reveal the underlying causal …
analysis. However, existing feature selection algorithms rarely reveal the underlying causal …
[PDF][PDF] An ensemble model to predict health insurance premium using machine learning
J Rampal, P Singh, R Kaur… - Dogo Rangsang …, 2020 - journal-dogorangsang.in
Health insurance is one of the most significant investments an individual makes every year.
Onethird of GDP is spent on health insurance, and everyone needs some level of health …
Onethird of GDP is spent on health insurance, and everyone needs some level of health …