Shevs Connect Institute | SCILabel | Medical AI Annotation Company & Ethical Data Marketplace https://validator.w3.org/feed/docs/rss2.html Blog Building RLHF evaluation rubrics and clinical AI style guides Corrective feedback writing for AI model improvement: what makes feedback actionable Red-teaming clinical AI: identifying harmful, biased and PHI-violating outputs Comparative ranking and preference annotation: methodology and justification writing Evaluating AI drug information, prescribing recommendations and pharmacovigilance outputs Evaluating AI clinical note generation and medical summarisation Evaluating AI clinical decision support and differential diagnosis outputs Evaluating AI radiology and pathology report outputs: missed findings and hallucinations The clinical AI evaluation framework: accuracy, safety, completeness and tone RLHF fundamentals: how human feedback trains clinical AI models Home AI-assisted image annotation: reviewing, accepting and correcting model pre-annotations Medical image annotation quality assurance: modality-specific errors and self-review checklists Paediatric imaging: age-specific anatomy, bone development and congenital abnormality labeling Cardiovascular imaging: coronary artery labeling, calcium scoring and cardiac CT Breast imaging: mammographic density, BI-RADS classification and microcalcification Nuclear medicine, PET/SPECT and fused imaging annotation Advanced segmentation: semantic vs instance segmentation and polygon annotation precision Surgical video and endoscopy annotation: frame-by-frame labeling of instruments and tissue Dental and oral radiology annotation: OPG, CBCT and common findings Dermatology and skin lesion classification: dermoscopy and the ABCDE criteria Ophthalmology image annotation: fundus photography, OCT and diabetic retinopathy grading Digital pathology and whole slide image (WSI) annotation: H&E staining, tumour and tissue labeling Ultrasound and echocardiography annotation: obstetric, abdominal, thyroid and cardiac MRI annotation: T1/T2/FLAIR/DWI sequences, brain lesions, spine and musculoskeletal CT scan annotation: slice navigation, windowing and lesion labeling across organ systems Chest X-ray annotation: normal anatomy, pneumonia, pleural effusion, nodules and pneumothorax DICOM format, metadata and medical image viewers: RadiAnt, Weasis and OsiriX setup guide Medical imaging modalities: X-ray, CT, MRI, ultrasound, PET and endoscopy — a visual annotator’s guide Swedish for Medical Professionals Cohort I-2026 Program Final Assesment Assignment 20 Assignment 19 Assignment 18 Assignment 17 General Swedish for Professionals A1-2026 SCI- HEALTHCARE AI TRAINER & DATA ANNOTATION PROGRAM Assignment 1 Assignment 2 Assignment 3 Assignment 4 Assignment 5 Assignment 6 Assignment 7 Final Assessment Assignment 16 Assignment 15 Assignment 14 Assignment 13