Author

S. Hasan Ali

University of LiverpoolORCID 0000-0003-4744-4963Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:benchmarking· 1 Assay:electronic health records· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Adarsh D. MakdaniiD· 1 shared Andrej StančákiD· 1 shared Andrew G. MarshalliD· 1 shared Christopher Andrew BrowniD· 1 shared Danielle HewittiD· 1 shared Francis P. McGloneiD· 1 shared Jessica Henderson· 1 shared Luidgi ThraceiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperNeuroscience

Adarsh D. MakdaniORCID

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2 papers

Recent·Most cited

NeuroscienceThe Journal of PhysiologyPeer-reviewedSep 23, 2026

The influence of force on the encoding and perception of affective touch

Sophia Faresse, Luidgi Thrace, S. Hasan Ali…·Rochelle Ackerley

This study investigates how force affects the pleasantness and intensity of stroking touch and the activity of C-LTMRs, finding that force modifies pleasantness and increases intensity with velocity.

DOI 10.1113/jp290946

humanexperimental assay

𝕏 PostBluesky

NeurosciencebioRxivPreprintNov 9, 2023

External Validation of Machine Learning and EEG for Continuous Pain Intensity Prediction in Healthy Individuals

Tyler Mari, Jessica Henderson, S. Hasan Ali…·Nicholas B. Fallon

This study externally validates machine learning models for predicting continuous pain intensity from EEG data in healthy individuals, finding limited accuracy despite some classification model success.

2 citations

humanelectronic health records

𝕏 PostBluesky