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2025

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Parkinson's Disease Detection Using Deep Learning Approach Based On Wearable Sensor-Based Daily Monitoring, Bahaulddin N. Adday, Khalid Shaker, Ihsan Salman, Hothefa Shaker Jan 2025

Parkinson's Disease Detection Using Deep Learning Approach Based On Wearable Sensor-Based Daily Monitoring, Bahaulddin N. Adday, Khalid Shaker, Ihsan Salman, Hothefa Shaker

Mesopotamian Journal of Artificial Intelligence in Healthcare

Parkinson's disease (PD) is a movement disorder characterized by motor dysfunction commonly bradyphemia, tremor, rigidity, akinesia, or slowness of movement. Noting that motor states can fluctuate in PD the primary aim of this current paper was to differentiate multiple states using wearable sensors in the patients and detection of this PD based on deep learning (CNN). Methodology: In this paper, the researchers recorded the signals of the accelerometer and gyroscope fixed on the wrist of PD in their regular daily functioning after using this dataset collection. The deep learning architecture developed was to optimize a CNN for analyzing the sensor …

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An Artificial Intelligence Model For Predicting Hospital Readmission Using Electronic Health Records Data, Rezarta Cara, Klodian Dhoska, Fjona Cara, Fredrick Kayusi, Linety Juma Jan 2025

An Artificial Intelligence Model For Predicting Hospital Readmission Using Electronic Health Records Data, Rezarta Cara, Klodian Dhoska, Fjona Cara, Fredrick Kayusi, Linety Juma

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study investigates the application of a machine learning model—specifically the Light Gradient Boosting Machine (LightGBM)—to predict 30-day hospital readmissions using structured electronic health record (EHR) data. Hospital readmissions remain a critical challenge in healthcare systems, often indicating gaps in continuity of care and contributing to higher costs. By leveraging demographic, clinical, and diagnostic variables from 350 anonymized patient records, the model aimed to accurately identify individuals at high risk of readmission. Key features included age, number of previous admissions, length of stay, number of medications, chronic disease status, and gender. Data preprocessing, model training, and evaluation were conducted using …

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Game-Based Recruitment Assessment, Hafsa Nasir, Maira Munir, Zara Mahroyan Kashif, Abdul Rafay, Zarlish Mohtasham Jan 2025

Game-Based Recruitment Assessment, Hafsa Nasir, Maira Munir, Zara Mahroyan Kashif, Abdul Rafay, Zarlish Mohtasham

BSCS Final Year Projects

The primary objective of our project is to develop a game-based recruitment system that modernizes traditional personality assessments by making them more engaging, adaptive, and relevant by incorporating real scenarios. We began by examining established models such as the Myers-Briggs Type Indicator (MBTI) and the Big Five personality traits. While these tools provide meaningful psychological insights, their formats are too lengthy, and repetitive. To address this, we selected approximately 20 questions most relevant to workplace behavior and hiring decisions and imitated the scoring process of the MBTI questionnaires. This not only shortens the assessment process but also improves candidate engagement. …

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