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Ali Kargarandehkordi

Showing results (1-10 of 8) with videos related to

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Applied Sciences (Basel, Switzerland)|August 7, 2025
Personalization of Affective Models Using Classical Machine Learning: A Feasibility StudyAli Kargarandehkordi, Matti Kaisti, Peter Washington
JMIR Research Protocols|March 25, 2024
Personalized AI-Driven Real-Time Models to Predict Stress-Induced Blood Pressure Spikes Using Wearable Devices: Proposal for a Prospective Cohort StudyAli Kargarandehkordi, Christopher Slade, Peter Washington
Biosensors|April 25, 2025
Fusing Wearable Biosensors with Artificial Intelligence for Mental Health Monitoring: A Systematic ReviewAli Kargarandehkordi, Shizhe Li, Kaiying Lin, et al.
JMIR Research Protocols|February 7, 2024
Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment StudyYinan Sun, Ali Kargarandehkordi, Christopher Slade, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|February 27, 2026
Barriers to Designing Inclusive Ecological Momentary Assessment and Wearable Data Collection Protocols for AI-Driven Substance Use Monitoring in Hawai'iYinan Sun, Aditi Jaiswal, Ali Kargarandehkordi, et al.
AI (Basel, Switzerland)|May 12, 2025
Monitoring Substance Use with Fitbit Biosignals: A Case Study on Training Deep Learning Models Using Ecological Momentary Assessments and Passive SensingShizhe Li, Chunzhi Fan, Ali Kargarandehkordi, et al.
JMIR Cancer|May 26, 2026
Correlates of Fitness Tracker Ownership and Use in Cancer Survivors: Cross-Sectional SurveyRoberto M Benzo, James L Fisher, Macy K Tetrick, et al.
Npj Mental Health Research|May 8, 2026
Personalized modeling of stress and blood pressure reactivity using mobile health dataAli Kargarandehkordi, Aditi Jaiswal, Agnik Banerjee, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
Applied Sciences (Basel, Switzerland)|August 7, 2025
Personalization of Affective Models Using Classical Machine Learning: A Feasibility StudyAli Kargarandehkordi, Matti Kaisti, Peter Washington
JMIR Research Protocols|March 25, 2024
Personalized AI-Driven Real-Time Models to Predict Stress-Induced Blood Pressure Spikes Using Wearable Devices: Proposal for a Prospective Cohort StudyAli Kargarandehkordi, Christopher Slade, Peter Washington
Biosensors|April 25, 2025
Fusing Wearable Biosensors with Artificial Intelligence for Mental Health Monitoring: A Systematic ReviewAli Kargarandehkordi, Shizhe Li, Kaiying Lin, et al.
JMIR Research Protocols|February 7, 2024
Personalized Deep Learning for Substance Use in Hawaii: Protocol for a Passive Sensing and Ecological Momentary Assessment StudyYinan Sun, Ali Kargarandehkordi, Christopher Slade, et al.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|February 27, 2026
Barriers to Designing Inclusive Ecological Momentary Assessment and Wearable Data Collection Protocols for AI-Driven Substance Use Monitoring in Hawai'iYinan Sun, Aditi Jaiswal, Ali Kargarandehkordi, et al.
AI (Basel, Switzerland)|May 12, 2025
Monitoring Substance Use with Fitbit Biosignals: A Case Study on Training Deep Learning Models Using Ecological Momentary Assessments and Passive SensingShizhe Li, Chunzhi Fan, Ali Kargarandehkordi, et al.
JMIR Cancer|May 26, 2026
Correlates of Fitness Tracker Ownership and Use in Cancer Survivors: Cross-Sectional SurveyRoberto M Benzo, James L Fisher, Macy K Tetrick, et al.
Npj Mental Health Research|May 8, 2026
Personalized modeling of stress and blood pressure reactivity using mobile health dataAli Kargarandehkordi, Aditi Jaiswal, Agnik Banerjee, et al.
Pageof 1