In the medical and drug discovery fields, the need for an automated process of diagnosing and evaluating cells has existed for many years. However, conventional image processing and analysis models have struggled to produce favorable results. Even with the introduction of AI, researchers have found it challenging to make significant advances using conventional “deep learning” models due to the need for large amounts of training data, case-by-case models, and “black box” issues.
HACARUS’ unique AI technology can solve these issues while simultaneously improving the speed and accuracy of cell diagnosis for both the medical and drug discovery fields. Through proprietary software and a lightweight model, the Cell Image Diagnosis is able to perform using small amounts of training data to swiftly produce models. The logic and decision-making of the HACARUS models can also be analyzed, further aiding to the development of future medicines
For medical professionals performing pathological diagnosis for breast and colorectal cancers, cell counting is a time intensive task which bottlenecks the entire process. HACARUS’ unique AI solves this problem, enabling fast and accurate cell detection and counting.
The main purpose of this system is to reduce the time required for discovering hit compounds and to identify the causative factors. HACARUS’ AI is also applied in phenotypic screening. As the training data is limited to images from control groups, modeling can be done quickly without sacrificing any accuracy.
