The following content is excerpted from the industry white paper "towards intelligent world 2024-data storage"

i, diagnosis and treatment to prevention: assist to improve diagnosis and treatment efficiency, accelerate rehabilitation and reduce diseases

with AI with the continuous development of technology, AI the combination with the medical industry is getting deeper and deeper, and its application in the medical field is becoming more and more extensive, AI the changes brought to the medical industry are more significant, from auxiliary diagnosis and treatment, drug research and development to disease early warning and other application scenarios, AI they all play an important role. Future, AI the development trend in the medical field will profoundly affect the pattern of the medical industry and the medical experience of patients.

Medical treatment+AI"Application scenario

1, auxiliary diagnosis and treatment

the application pilot of AI technology in primary health and health services was launched and implemented, forming a replicable medical artificial intelligence primary auxiliary diagnosis and treatment application system. Through intelligent triage, AI assist diagnosis and treatment and other methods to help doctors improve the diagnosis and treatment level and empower primary diagnosis and treatment. For example, a AI the equipment of intelligent segmentation and planning algorithm is suitable for clinical scenarios such as aspiration and drainage of cerebral hemorrhage, intracranial biopsy, etc. Through AI find the plaque location, accurately locate the cerebral hemorrhage point, assist the doctor to complete the operation, and improve the safety and accuracy of the operation.

2 drug research and development

traditional drug innovation research and development follows the "inverted Moore's Law", AI the advantages of technology through data and algorithm model building are bringing revolutionary changes to drug research and development. Through deep learning models, molecular structures can be analyzed more quickly, thus accelerating the discovery of new drugs and reducing expensive experimental requirements. For example, there are studies using AI successfully identified a drug that can resist antibiotic-resistant bacteria21 found within days, and in46 the experimental verification was completed within days, which was several years faster than the traditional drug research and development process and greatly shortened the time and cost of drug research and development.

3 disease warning

the application of AI and big data models has provided "tools" for disease early warning ". By analyzing the information and information of various diseases in the International Health Department, help the departments of Disease Control and Prevention to predict the development trend and high incidence period of diseases more accurately, so as to take corresponding prevention and control measures in advance. For example, AI it can "collect" subtle information that cannot be recognized by ophthalmologists, analyze retinal changes of patients with certain diseases through big data models, and finally complete disease detection tasks with clear markers.

II, connect diagnosis and treatment data sharing, protect data security, and maintain patient privacy

with AI with the wide application of technology in the medical field, the data in the medical industry is also facing many challenges such as difficult data collection, data privacy and security, and being attacked by ransomware viruses.

1. Difficulty in data collection

AI feeds on data. The more data it obtains, the better the quality, and the better it can perform in tasks. The data collected must come from reliable sources. Collecting data from unreliable sources may AI the output of the training has adverse effects. Therefore, in order to obtain accurate output, hospitals must collect training data from reliable sources, such as finding reliable data from patients' history and current medical records.

2 data privacy and security

the medical field involves a large number of sensitive data, such as patient's identity information, health status, disease diagnosis and treatment, biological gene information, etc., which not only involves patient privacy, but also has special sensitivity and important value, once leaked, it may bring physical and mental distress and property loss to patients, and even have a negative impact on social stability and national security. Therefore, data security in the medical field is very important.

However, medical treatment AI the research and development and application of must rely on a large amount of medical data for algorithm training. The larger and more diverse the data volume, the more accurate the analysis and prediction results will be. However, the application of big data technologies such as data collection, analysis and processing, cloud storage and information sharing increases the risk of data leakage.

3, attacked by ransomware virus

the development of AI technology makes blackmail software more accurate in selecting targets, customizing attacks, and more deceptive. By analyzing the target data and behavior patterns, blackmail software can select targets more effectively and formulate more targeted attack strategies. In addition, AI it can make blackmail software more adaptive in the attack process, adjust the attack mode according to the victim's reaction, and increase the probability of successful attack. 《2023 according to the analysis report on the attack situation of ransomware by Chinese enterprises in, the medical industry has become the hardest hit area for ransomware attacks. From2018 it has happened all over the world since500 the second publicly confirmed blackmail software attack against medical organizations, resulting in near1.3 tens of thousands of independent facilities were paralyzed and affected nearly4900 tens of thousands of patient records, the economic losses caused by downtime alone have exceeded920$100 million. According to third-party statistics, the medical industry continues12 it became the industry with the highest cost of data leakage in,2022 the data of medical institutions reached as high1010 ten thousand dollars, and2020 year-on-year surge42%.

Analysis Report on attack situation of Blackmail virus in Chinese enterprises in 2023

in order to effectively solve many data challenges, the medical industry urgently needs to adopt professional data storage products, through professional storage endogenous security, disaster recovery backup, secure and trusted data flow, anti-ransomware protection technology, etc., to save data, save, use, and help AI accelerate the medical field to the intelligent world.