What are the medical data sets that I can use to train AI for medical diagnosis?
AI in medical diagnosis is can help doctors to detect various types of diseases automatically without radiologists. X-rays, CT Scan and MRI are the medical imaging used to diagnosis the diseases with the help AI-enabled devices, applications or system trained with high-quality training data.
There are many medical data sets that can be used to train for medical diagnosis for different types of diseases. For AI in medical diagnosis mainly annotated data sets ate used to train the AI model that can learn how to detect the various ailments with acceptable level of accuracy. Here you can find below types of medical data sets you can use to train the AI model for medical diagnosis.
Types of Medical Data Sets for AI in Medical Diagnosis:
· Polygon Annotation for AI in Dentistry
· Training data to Detect the Brain Tumor
· Training data Neurological Abnormalities
· Training data for Breast Cancer Diagnosis
· Annotated X-ray Images for bone fracture diagnosis
· Bounding Box annotation for kidney stone detection
· Semantic segmentation annotation for prostate cancer
Also Read : What are the Types of Diagnostic Imaging Used for AI in Medical Diagnosis: Use Cases
Medical imaging data annotated with image annotation services can provide the training data sets to train the AI models. As per the different image annotation techniques, different types of training data sets can be created for various AI models developed or used for medical diagnosis. Medical training data sets are created for computer vision based machine learning models trained through such data sets.
Anolytics provide the medical imaging data sets
for machine learning training and AI model development. With data annotation services, Anolytics offers image annotation services to create the high-quality training data used to train the AI model for medical diagnosis. It is working with highly experienced annotators to annotate the medical images with high accuracy for right diagnosis.
