Research Aim
Clinical and care settings generate many kinds of data, including medical images, sensor measurements, gaze data, lifestyle records, schedules, and simulation outputs. Our goal is to turn these heterogeneous data sources into systems that help people make better decisions.
Hariyama Laboratory combines AI, mathematical optimization, visualization, and high-performance computing to support diagnosis, surgery, evaluation, care planning, and data-driven medical discovery.
Research Topics
Liver Surgery Support System
We integrate CT images, ultrasound images, and position sensors to support preoperative planning and intraoperative navigation for liver resection.
Read moreOral Surgery Support System
We study surgical navigation, robotic positioning, VR/AR-based training, and AI-based evaluation for oral and maxillofacial surgery.
Read moreAI Assessment of Children's Reading Ability
We analyze eye-tracking data during oral reading to detect reading behaviors and support early assessment of reading difficulties.
Read moreMedical Big Data Analysis
We use machine learning, explainable AI, and causal modeling to analyze clinical, body composition, and lifestyle data.
Read moreHome-Care Scheduling
We explore optimization-based decision support for monthly home-care schedules while considering staff continuity, time windows, and travel time.
Read moreCell Multi-Agent Simulation
We model cells as interacting agents and analyze how cellular communities form, persist, and change over time.
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