1 citations · 1 across the 4 of their papers we have counts for
5 papers
Evaluating TabPFN for Mild Cognitive Impairment to Alzheimer's Disease Conversion in Data Limited Settings
Brad Ye, Bulent Soykan, Gulsah Hancerliogullari Koksalmis +2
Accurate prediction of conversion from Mild Cognitive Impairment (MCI) to Alzheimers Diseases (AD) is essential for early intervention, however, developing reliable conversion pred…
Toward Personalized Digital Twins for Cognitive Decline Assessment: A Multimodal, Uncertainty-Aware Framework
Bulent Soykan, Gulsah Hancerliogullari Koksalmis, Hsin-Hsiung Huang +1
Cognitive decline is highly heterogeneous across individuals, which complicates prognosis, trial design, and treatment planning. We present the Personalized Cognitive Decline Asses…
CognitiveTwin: Robust Multi-Modal Digital Twins for Predicting Cognitive Decline in Alzheimer's Disease
Bulent Soykan, Gulsah Hancerliogullari Koksalmis, Hsin-Hsiung Huang +1
Predicting individual cognitive decline in Alzheimer's disease (AD) is difficult due to the heterogeneity of disease progression. Reliable clinical tools require not only high accu…
Integrating Metaverse Technologies in Medical Education: Examining Acceptance Factors Among Current and Future Healthcare Providers
Seckin Damar, Gulsah Hancerliogullari Koksalmis
This study investigates behavioral intention to use healthcare metaverse platforms among medical students and physicians in Turkey, where such technologies are in early stages of a…
Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions
Gulsah Hancerliogullari Koksalmis, Bulent Soykan, Laura J. Brattain +1
Alzheimer's Disease (AD) is marked by significant inter-individual variability in its progression, complicating accurate prognosis and personalized care planning. This heterogeneit…