Masaharu Nakayama

Professor

Tohoku University

Japan

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Professor Masaharu Nakayama is a faculty member at Tohoku University in Japan. His research areas include health informatics, disaster management in healthcare, and machine learning applications in medical data analysis. Recent publications focus on enhancing personal health record systems, implementing international patient summary protocols, and developing predictive models for respiratory failure in ICU patients. Professor Nakayama is actively engaged in advancing healthcare interoperability and improving patient data management through innovative technological solutions.

Articles (14)

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

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2021

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2020

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2020

Collaborators (4)

Rintaro Moroi

Tohoku University Hospital

JAPAN

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SUSUMU FUJII

Associate Professor

Tohoku University

JAPAN

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Yoichi Kakuta

Tohoku University Hospital

JAPAN

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Shinichiroh Yokota, RN, PHN, PhD

Assistant Professor

University of Tokyo

JAPAN

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Masaharu Nakayama

Research Interests

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Articles (14)

Implementation of the World Health Organization Minimum Dataset for Emergency Medical Teams to Create Disaster Profiles for the Indonesian SATUSEHAT Platform Using Fast Healthcare Interoperability Resources: Development and Validation Study

Enhancing the Functionalities of Personal Health Record Systems: Empirical Study Based on the HL7 Personal Health Record System Functional Model Release 1

Collection of patient-generated health data with a mobile application and transfer to hospital information system via QR codes

Implementation of a Patient Summary Web Application According to the International Patient Summary and Validation in Common Use Cases in Japan

Prediction of respiratory failure risk in patients with pneumonia in the ICU using ensemble learning models

Hemodialysis Record Sharing: Solution for Work Burden Reduction and Disaster Preparedness

Associations among cardiovascular and cerebrovascular diseases: Analysis of the nationwide claims-based JROAD-DPC dataset

Machine learning models to detect social distress, spiritual pain, and severe physical psychological symptoms in terminally ill patients with cancer from unstructured text data in electronic medical records

Validity of identification algorithms combining diagnostic codes with other measures for acute ischemic stroke in MID-NET®

Development of an application concerning fast healthcare interoperability resources based on standardized structured medical information exchange version 2 data

Health Information Exchange between Specialists and General Practitioners Benefits Rural Patients

Use of medical information and digital services for self-empowerment before, during, and after a major disaster

Standard Export Data Format for Extension Storage of Standardized Structured Medical Information Exchange

Incorporating Tacit Knowledge of Experts in the Assessment of Shelters Under Disaster

Collaborators (4)

Rintaro Moroi

SUSUMU FUJII

Yoichi Kakuta

Shinichiroh Yokota, RN, PHN, PhD

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