DeepAI AI Chat
Log In Sign Up

AI and Pathology: Steering Treatment and Predicting Outcomes

06/15/2022
by   Rajarsi Gupta, et al.
0

The combination of data analysis methods, increasing computing capacity, and improved sensors enable quantitative granular, multi-scale, cell-based analyses. We describe the rich set of application challenges related to tissue interpretation and survey AI methods currently used to address these challenges. We focus on a particular class of targeted human tissue analysis - histopathology - aimed at quantitative characterization of disease state, patient outcome prediction and treatment steering.

READ FULL TEXT

page 3

page 5

12/17/2021

Towards Launching AI Algorithms for Cellular Pathology into Clinical Pharmaceutical Orbits

Computational Pathology (CPath) is an emerging field concerned with the ...
02/06/2023

Studying Therapy Effects and Disease Outcomes in Silico using Artificial Counterfactual Tissue Samples

Understanding the interactions of different cell types inside the immune...
10/27/2019

Deep Learning Models for Digital Pathology

Histopathology images; microscopy images of stained tissue biopsies cont...
09/22/2020

Qlib: An AI-oriented Quantitative Investment Platform

Quantitative investment aims to maximize the return and minimize the ris...
06/11/2023

Computational Language Assessment: Open Brain AI

Language assessment plays a crucial role in diagnosing and treating indi...