Widely used in medical data analysis, medical management, etc.

Google’s liver cancer screening algorithm uses SVM to extract pixel-level features to effectively identify tumor and non-tumor regions

Microsoft's innerEye uses DT to process image data to determine the patient's likelihood of illness and the type of disease.

IBM Watson uses a random forest algorithm to select high-confidence trajectory paths from a large number of patient records to assist doctors in formulating treatment plans.

GE Healthcare uses deep learning technology to improve diagnostic efficiency of medical imaging

Tempus Labs analyzes large amounts of patient data and genetic data to predict a patient's risk of cancer and tumors

IBM Watson uses technologies such as KNN to analyze patients' clinical data and health records to predict possible disease risks

Luminex uses HMM to develop tools for protein interaction analysis and genotype analysis

Aidoc uses VAE to automatically generate reports on X-rays and CT scans

DeepMind partners with Moorfields Eye Hospital to develop medical image generator using GAN technology

The industry has accumulated rich human experience

Experience can be quantified and defined as algorithms

Experience must be graded to be able to judge whether it is good or bad.

Although massive amounts of data have been accumulated in the field of drug development, even more remains unknown.

We have some crude classification and quantification of some diseases, but quantitative measurements of health and phenotypes are just beginning.

There is some classification of pros and cons and positive and negative feedback that can be used to optimize experience, but it is far from enough and the feedback cycle is long.

In the early stages of development, technology faces challenges with data algorithms and talent, and its role in drug discovery is limited to speed and cost rather than the quality of decision-making.

Drug research and development is a long process, and there is an irreconcilable contradiction between the speed of AI and the slowness of pharmaceuticals.

Protein engineering, AI for protein design

Hiring others to obtain services is becoming increasingly expensive

Ownership lies with the individual, control lies with the hospital, and management lies with the government

The company and the hospital sign a research and development agreement to obtain it. The data is not discharged, but the model is discharged.