Yogesh T.

Key Skills

Software

Other

Top Subject Matter

Medical imaging disease prediction (X-ray)

AI fundamentals and AI-enabled web project development

Top Data Types

Image

Text

Top Task Types

Diagnosis

Data Collection

Freelancer Overview

Front End Developer — medical predictions system using X-ray images. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and Google Colab. Education includes Secondary School Certificate, Tjs Matric Higher Secondary School Tiruvallur (2021) and Higher Secondary School Certificate, Tjs Matric Higher Secondary School Tiruvallur (2023). AI-training focus includes data types such as Medical, DICOM, and Computer Code and labeling workflows including Diagnosis and Data Collection.

Labeling Experience

Learning (Online) — fundamentals of Artificial Intelligence

Data Collection

Completed learning focused on practical AI fundamentals and how to apply AI concepts in small web projects. The work included exploring machine learning basics and building simple AI-enabled recommendation functionality. This provided hands-on exposure to AI tooling and problem-solving workflows, supporting future AI training and data preparation habits. • Explored machine learning basics and AI-powered solutions. • Developed a simple web-based project integrating AI features (recommendations). • Built a basic website demonstrating AI usage for real-world recommendations (e.g., food). • Gained hands-on experience using AI tools to solve problems.

2025 - Present

Front End Developer — medical predictions system using X-ray images

OtherDiagnosis

Worked on a medical image–based disease prediction interface using X-ray images for real-time clinical-like results. The work involved preparing and validating the end-to-end prediction workflow tied to outputs for conditions such as tuberculosis, COVID-19, and fibrosis. This effort required careful handling of medical imagery and ensuring the model predictions were correctly displayed to users. • Built a UI to present prediction results for multiple diseases. • Integrated the frontend with a backend model for real-time disease prediction. • Focused on usability and accuracy improvements for the prediction system. • Collaborated with a team to refine the disease prediction experience.

2025 - Present

Education

Work History