Diagnostic AI for Blood & Pathology
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About this role
Data Processing, Machine Learning (ML), Data Science, Tensorflow, Pytorch, Data Integration, Natural Language Processing, Data Annotation · I am building an AI-driven application that supports medical diagnostics by reading raw blood-test and pathology reports, extracting the relevant figures, and instantly returning an easy-to-read interpretation along with evidence-based clinical suggestions.
The core workflow is straightforward: a clinician (or patient) uploads a PDF, image, HL7/FHIR payload, or even a snapped photo of a report; the system recognises the data, checks each finding against reference ranges, flags abnormalities, and explains the potential implications in plain language. Where results form recognisable patterns (for example, anaemia profiles or inflammatory markers) the model should surface likely differential diagnoses and recommended next-step investigations.
To get there I will need robust OCR or direct-feed parsing, a well-trained ML/NLP pipeline (TensorFlow, PyTorch or similar), and a lightweight cross-platform front-end—web first, with mobile to follow. Clinical accuracy, privacy (HIPAA / GDPR), and clear audit trails for every prediction are non-negotiable.
Please send me a detailed project proposal covering architecture, data-set strategy, validation metrics, regulatory safeguards, timeline,