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AI for Pathology

AI can help Pathologists quickly extract insights from Pathological imagery like Tissue Slides, leading to much faster and more accurate diagnosis. This can help them scale their workloads instead of spending significant time manually analyzing those images 

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1. Get Inspired

Understand the Use-case under 5 minutes

2. Know More

Get to know more Business and Technical details about the use-case (15-30 minutes)

Deeper Intro

More detailed introduction covering business and technical aspects

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

Tech focused

More details on the technical aspects of the use-case

3. Do

Technical resources that will help you implement the use-case (notebooks, tutorials..)

Data Sets

Data Sets you can use to build Demos, POCs, or test Algorithms


Breast Cancer Metastases In Lymph Nodes Provided By Grand Challenge For Detection And Classification Of Breast Cancer Metastases In Whole-Slide Images Of Histological Lymph Node Sections

Lung And Colon Cancer Histopathological Images

25,000 Images Of 5 Classes Including Lung And Colon Cancer & Healthy Samples. There Are Five Classes In The Dataset, each with 5,000 Images

Breast Cancer Histopathological Database (Breakhis)

The Breast Cancer Histopathological Image Classification (Breakhis) Is Composed Of 9,109 Microscopic Images Of Breast Tumor Tissue Collected From 82 Patients Using Different Magnifying Factors


Off-the-Shelf Products using AI for Pathology Sample Analysis

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