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E

Eisuke Kanematsu

Medical Doctor – AI Training & Clinical Annotation

JAPAN flag
Tokyo, Japan
$70.00/hrEntry Level

Key Skills

Software

No software listed

Top Subject Matter

Clinical Medicine
Rheumatology Domain Expertise
Internal Medicine

Top Data Types

ImageImage
TextText
DocumentDocument

Top Task Types

Diagnosis
Red Teaming
RLHF

Freelancer Overview

Medical Doctor – AI Training & Clinical Annotation. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Master of Public Health, The University of Tokyo (2028 expected) and Doctor of Medicine, Nagoya City University (2017). AI-training focus includes data types such as Medical and DICOM and labeling workflows including Diagnosis.

Entry LevelEnglishJapanese

Labeling Experience

Medical Doctor – AI Training & Clinical Annotation

Diagnosis
Served as a medical doctor specializing in AI model training, clinical data annotation, and medical dataset curation for healthcare-related projects. Reviewed EHR charts, performed structured clinical annotation, and contributed to evidence-based labeling for use in AI applications. Ensured label consistency and diagnostic accuracy for medical data to train and validate clinical decision-support systems. • Conducted detailed case-level annotation of EHR, imaging, and structured medical data • Verified and labeled reasoning processes for differential diagnosis tasks • Collaborated with data science teams on annotation protocol development • Participated in QA and consistency review to enhance dataset reliability

Served as a medical doctor specializing in AI model training, clinical data annotation, and medical dataset curation for healthcare-related projects. Reviewed EHR charts, performed structured clinical annotation, and contributed to evidence-based labeling for use in AI applications. Ensured label consistency and diagnostic accuracy for medical data to train and validate clinical decision-support systems. • Conducted detailed case-level annotation of EHR, imaging, and structured medical data • Verified and labeled reasoning processes for differential diagnosis tasks • Collaborated with data science teams on annotation protocol development • Participated in QA and consistency review to enhance dataset reliability

2023 - Present

Education

T

The University of Tokyo

Master of Public Health, Public Health

Master of Public Health
2026 - 2026
N

Nagoya City University

Doctor of Medicine, Medicine

Doctor of Medicine
2010 - 2017

Work History

T

Tokyo Metropolitan Tama-Nambu Chiiiki Hospital

Attending Physician, Rheumatology

Tokyo
2023 - Present
T

Tokyo Metropolitan Tama Medical Center

Internal Medicine and Rheumatology Fellow

Tokyo
2019 - 2023