Dr. A.

Key Skills

Software

Internal/Proprietary Tooling

Other

Top Subject Matter

Radiology Domain Expertise

Oncology Domain Expertise

Bone Tumors

Top Data Types

Image

Medical Dicom

Text

Top Task Types

Classification

Diagnosis

Evaluation/Rating

Segmentation

Entity (NER) Classification

Object Detection

Data Collection

Freelancer Overview

Doctoral Researcher - AI in Bone Tumor Diagnosis. Brings 6+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Doctor of Philosophy, N/A (2025) and Specialist Training in Radiology, La Fe Polytechnic University Hospital (2026). AI-training focus includes data types such as Medical and DICOM and labeling workflows including Classification and Diagnosis.

Labeling Experience

Data Labeling and Annotation for Bone Tumor AI

Medical DicomSegmentation

In doctoral research, annotated and reviewed medical images related to bone tumor diagnosis for training machine learning models. Evaluated AI-generated outcomes for classification and prognosis tasks, focusing on sarcoma identification and risk stratification. Collaborated with supervisors to iteratively improve dataset quality and annotation standards. • Responsible for detailed reviews of labeled DICOM images for AI model training. • Documented inconsistencies and errors in AI-generated labels for correction cycles. • Assisted in dataset curation for multi-institutional AI studies in oncology. • Used in-house annotation and data management tools integrated with hospital systems.

2025 - Present

Doctoral Researcher - AI in Bone Tumor Diagnosis

Medical DicomEntity (NER) Classification

During doctoral research, contributed to AI system development and validation for classifying bone tumors and predicting bone sarcoma prognosis. Responsibilities included assisting with data annotation strategy, evaluation of model predictions, and radiology image review for correctness. Provided feedback to technical teams on labeling quality and model performance. • Involved in establishing annotation guidelines with medical domain experts. • Participated in external validation and testing of AI models on new datasets. • Engaged in quality assurance for labeled datasets, ensuring diagnostic accuracy and consistency. • Worked with proprietary software within the hospital IT infrastructure.

2025 - Present

Radiologist – AI Workflow Validation and Annotation

Medical DicomEvaluation/Rating

Supported validation and external testing of AI-assisted radiology workflows in a tertiary hospital setting from 2022 onwards. Tasks included reviewing AI predictions on medical images, contributing radiology expertise for model improvement, and participating in feedback cycles for continual AI workflow enhancement. Provided input for annotation accuracy and assisted clinical teams in understanding AI integration in practice. • Engaged in multidisciplinary teams to assess AI workflow effectiveness in clinical applications. • Contributed to the refinement of AI model outputs based on observed clinical discrepancies. • Participated in scientific and clinical meetings focused on AI integration. • Utilized internal proprietary software tailored for radiological data handling and labeling.

2022 - Present

Education

Work History