Samaneh Kouchaki

Lecturer

University of Surrey

United Kingdom

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Samaneh Kouchaki is a Lecturer at the University of Surrey in the United Kingdom. Her research areas encompass biomedical language processing, machine learning applications in healthcare, and the early detection of diseases. Recent publications include work on effective instruction tuning in biomedical contexts, remote monitoring for urinary tract infections, and AI-driven solutions for COVID-19 screening. Dr. Kouchaki aims to contribute to advancements in health monitoring and predictive analytics through innovative methodologies.

Articles (13)

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2024

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2024

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2023

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2023

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2022

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2022

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2021

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2021

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2021

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2021

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2020

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2020

Collaborators (4)

Baptiste Vasey

University of Oxford

UNITED KINGDOM

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Ramin Nilforooshan

Professor in Psychiatry

University of Surrey

UNITED KINGDOM

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Ayse Demirkan

Senior Lecturer

University of Surrey

UNITED KINGDOM

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Timothy Walker

University of Oxford

UNITED KINGDOM

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Samaneh Kouchaki

Research Interests

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Articles (13)

Digital remote monitoring for screening and early detection of urinary tract infections

Exploring the effectiveness of instruction tuning in biomedical language processing

Privacy-Aware Early Detection of COVID-19 Through Adversarial Training

Machine Learning to Advance Human Genome-Wide Association Studies

An Unsupervised Data-Driven Anomaly Detection Approach for Adverse Health Conditions in People Living With Dementia: Cohort Study

A Dopamine Based Adaptive Emotional Neural Network

An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction.

Development and validation of early warning score systems for COVID-19 patients.

Analysing behavioural changes in people with dementia using in-home monitoring technologies

Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test

GenomegaMap: Within-Species Genome-Wide d<sub>N</sub>=d<sub>S</sub> Estimation from over 10,000 Genomes

Machine Learning Techniques for Soybean Charcoal Rot Disease Prediction.

Rapid triage for COVID-19 using routine clinical data for patients attending hospital: development and prospective validation of an artificial intelligence screening test.

Collaborators (4)

Baptiste Vasey

Ramin Nilforooshan

Ayse Demirkan

Timothy Walker

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