Godlyseed U.

Key Skills

Software

Don't disclose

Top Subject Matter

Clinical NLP for oncology and clinical trial outcome prediction

Top Data Types

Text

Top Task Types

Entity (NER) Classification

Freelancer Overview

Master's thesis: multimodal machine learning framework for clinical trial outcome prediction with explainability and str. Core strengths include Don't disclose. Education includes Bachelor of Arts, N/A and Master of Science, Nova School of Business and Economics. AI-training focus includes data types such as Text and labeling workflows including Entity (NER) Classification.

Labeling Experience

Master's thesis: multimodal machine learning framework for clinical trial outcome prediction with explainability and structured clinical knowledge extraction

Don't discloseTextEntity (NER) Classification

Used clinical natural-language processing on unstructured oncology/clinical trial reports to extract structured signals for downstream prediction tasks. The work involved converting free-text protocols and clinical features into model-ready representations while handling missingness and ensuring robust, leakage-controlled evaluation. Explainability was integrated to attribute predictions to clinically relevant features across phases. • Extracted structured signal from free-text clinical trial reports • Managed missing data and uncertainty in real-world text • Designed leakage-controlled pipeline with out-of-distribution evaluation • Added SHAP-based phase-level interpretability and feature stability checks

2023 - 2024

Education