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While electroencephalogram (EEG) has been a crucial tool for monitoring the brain and diagnosing neurological disorders (e.g., epilepsy), learning meaningful representations from raw EEG signals remains challenging due to limited…

Machine Learning · Computer Science 2025-09-03 Jia Hong Puah , Sim Kuan Goh , Ziwei Zhang , Zixuan Ye , Chow Khuen Chan , Kheng Seang Lim , Si Lei Fong , Kok Sin Woon , Cuntai Guan

Objective: Most current wearable tonic-clonic seizure (TCS) detection systems are based on extra-cerebral signals, such as electromyography (EMG) or accelerometry (ACC). Although many of these devices show good sensitivity in seizure…

Continuous electroencephalography (EEG) is routinely used in neurocritical care to monitor seizures and other harmful brain activity, including rhythmic and periodic patterns that are clinically significant. Although deep learning methods…

Human-Computer Interaction · Computer Science 2026-01-05 Argha Kamal Samanta , Deepak Mewada , Monalisa Sarma , Debasis Samanta

Treatment effect estimation (TEE) is the task of determining the impact of various treatments on patient outcomes. Current TEE methods fall short due to reliance on limited labeled data and challenges posed by sparse and high-dimensional…

Machine Learning · Computer Science 2024-03-07 Ruoqi Liu , Lingfei Wu , Ping Zhang

Accurate recognition of human emotional states is critical for effective human-machine interaction. Electroencephalography (EEG) offers a reliable source for emotion recognition due to its high temporal resolution and its direct reflection…

Machine Learning · Computer Science 2026-01-30 Maryam Mirzaei , Farzaneh Shayegh , Hamed Narimani

Transcranial magnetic stimulation co-registered with electroencephalographic (TMS-EEG) has previously proven a helpful tool in the study of Alzheimer's disease (AD). In this work, we investigate the use of TMS-evoked EEG responses to…

Epoetin is commonly used to treat anemia in chronic kidney disease and End Stage Renal Disease subjects undergoing dialysis, however, there is considerable uncertainty about what level of hemoglobin or hematocrit should be targeted in these…

Applications · Statistics 2015-02-04 Cecilia A. Cotton , Patrick J. Heagerty

Conditional average treatment effects (CATEs) allow us to understand the effect heterogeneity across a large population of individuals. However, typical CATE learners assume all confounding variables are measured in order for the CATE to be…

Machine Learning · Computer Science 2022-02-01 Yao Zhang , Jeroen Berrevoets , Mihaela van der Schaar

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children, characterized by difficulties in attention, hyperactivity, and impulsivity. Early and accurate diagnosis of ADHD is critical for effective…

Signal Processing · Electrical Eng. & Systems 2025-04-08 Md Bayazid Hossain , Md Anwarul Islam Himel , Md Abdur Rahim , Shabbir Mahmood , Abu Saleh Musa Miah , Jungpil Shin

Background: Depression in people with bipolar disorder is a major cause of long-term disability, possibly leading to early mortality and currently, limited safe and effective therapies exist. A double-blinded randomized placebo-controlled…

Quantitative Methods · Quantitative Biology 2020-11-12 Antoine Nzeyimana , Kate EA Saunders , John R Geddes , Patrick E McSharry

\noindent\textbf{Background} Prenatal glucocorticoid exposure alters cardiac development, but whether persistent cardiac effects in childhood follow a dose-response relationship remains unknown. We recently showed that ECG foundation models…

Quantitative Methods · Quantitative Biology 2026-03-05 Nicolas B. Garnier , Michelle Dreiling , Valeska Kozik , Matthias Schwab , Florian Rakers , Martin G Frasch

Response variability limits the clinical utility of transcutaneous auricular vagus nerve stimulation (taVNS) for negative symptoms in treatment-resistant schizophrenia (TRS). This study aimed to develop an electroencephalography (EEG)-based…

This paper introduces an innovative approach to Attention-deficit/hyperactivity disorder (ADHD) diagnosis by employing deep learning (DL) techniques on electroencephalography (EEG) signals. This method addresses the limitations of current…

Computers and Society · Computer Science 2024-12-04 Medha Pappula , Syed Muhammad Anwar

Background: Direct electrical stimulation of the brain through intracranial electrodes is currently used to probe the epileptic brain as part of pre-surgical evaluation, and it is also being considered for therapeutic treatments through…

Neurons and Cognition · Quantitative Biology 2020-11-18 Christoforos A Papasavvas , Gabrielle M Schroeder , Beate Diehl , Gerold Baier , Peter N Taylor , Yujiang Wang

Predicting and understanding the changes in cognitive performance, especially after a longitudinal intervention, is a fundamental goal in neuroscience. Longitudinal brain stimulation-based interventions like transcranial direct current…

Human-Computer Interaction · Computer Science 2024-02-01 Akash K Rao , Shashank Uttrani , Vishnu K Menon , Darshil Shah , Arnav Bhavsar , Shubhajit Roy Chowdhury , Varun Dutt

Major Depressive Disorder (MDD) is a highly prevalent mental health condition, and a deeper understanding of its neurocognitive foundations is essential for identifying how core functions such as emotional and self-referential processing…

End-stage chronic kidney disease (CKD) patients are facing a 30% rise for the risk of lethal cardiac events (LCE) compared to non-CKD patients. At the same time, these patients undergoing dialysis experience shifts in the potassium…

Signal Processing · Electrical Eng. & Systems 2020-06-11 Nicolas Pilia , Cristiana Corsi , Stefano Severi , Olaf Dössel , Axel Loewe

For a number of antiarrhythmics, drug loading requires a 3 day hospitalization with monitoring for QT prolongation. Automated QT monitoring with wearable ECG monitors would facilitate out-of-hospital care. We develop a deep learning model…

Signal Processing · Electrical Eng. & Systems 2024-08-13 Ridwan Alam , Aaron Aguirre , Collin Stultz

The electrocardiogram (ECG) is a key diagnostic tool in cardiovascular health. Single-lead ECG recording is integrated into both clinical-grade and consumer wearables. While self-supervised pretraining of foundation models on unlabeled ECGs…

Machine Learning · Computer Science 2025-12-03 Yuxuan Shu , Peter H. Charlton , Fahim Kawsar , Jussi Hernesniemi , Mohammad Malekzadeh

Repetitive Transcranial Magnetic Stimulation (rTMS) is a well-supported, evidence-based treatment for depression. However, patterns of response to this treatment are inconsistent. Emerging evidence suggests that artificial intelligence can…

Machine Learning · Computer Science 2024-04-29 Matthew Squires , Xiaohui Tao , Soman Elangovan , Raj Gururajan , Haoran Xie , Xujuan Zhou , Yuefeng Li , U Rajendra Acharya
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