Arup R.

Key Skills

Software

No software listed

Top Subject Matter

Cardiology (ECG, arrhythmia triage)

General medicine & multi-specialty clinical data for AI training context

Top Data Types

Text

Image

Document

Top Task Types

Diagnosis

Data Collection

Segmentation

Classification

Object Detection

Text Summarization

Evaluation/Rating

Text Generation

Question Answering

Point/Key Point

Freelancer Overview

Resident Medical Officer — Cardiology Department (clinical ground-truthing and validation for ECG AI). Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Bachelor of Medicine and Bachelor of Surgery, Calcutta National Medical College & Hospital (2026) and Honours Degree in Ophthalmology, West Bengal University of Health Sciences (WBUHS) (2026). AI-training focus includes data types such as Medical and DICOM and labeling workflows including Diagnosis and Data Collecti

Labeling Experience

Resident Medical Officer — Cardiology Department (clinical ground-truthing and validation for ECG AI)

Diagnosis

As a current Cardiology RMO, the work supports supervised-learning datasets through clinical ground-truthing. The role includes validating AI outputs by interpreting diagnostic sensitivity and specificity in a cardiology workflow. It also contributes to dataset curation and model validation with clinician-in-the-loop review. • Perform and interpret 12-lead ECGs relevant to ECG AI platforms • Provide clinical validation for AI outputs (sensitivity/specificity interpretation) • Support dataset curation and model validation with ground-truth labeling • Apply cardiac emergency context to improve clinical workflow integration

2026 - Present

Compulsory Rotatory Intern (clinical data exposure supporting AI training/annotation readiness)

Data Collection

During compulsory rotational internship, clinical exposure across multiple specialties supports gathering and preparing clinical data that can be used for AI training. The experience provides broad clinical context for applying labeling and validation principles across general medical AI tools. This includes physician-led participation in community health settings where structured collection may inform population health model training. • Rotations across Medicine, Surgery, Ophthalmology, Paediatrics, O&G and other departments • Build multi-specialty clinical data familiarity for multi-modal AI development • Participate in medical and blood donation camps as an attending physician • Support structured collection concepts relevant to population health AI

2025 - 2026

Education

Work History