Electronic Enthusiast Network Report (Text/Li Wanwan) "Natural A study recently published in Communications reveals a new platform for discovering cellular signatures of disease. NYSCF (New York Stem Cell Foundation) partnered with Google to successfully identify new cellular signatures of Parkinson's disease by creating and analyzing more than one million images of skin cells from 91 patients and healthy controls.

For complex diseases like Parkinson's, where traditional drug discovery doesn't work very well, the NYSCF-built robot enables research Humans are able to generate vast amounts of data from large numbers of patients and discover new disease signatures. The researchers hope their platform will open up new treatment avenues for many diseases for which traditional drug discovery has been unsuccessful.

NYSCF's senior vice president of discovery and platform development, Dr. Daniel Paull, said this is the first successful A tool to characterize disease and its ability to identify subgroups of patients has important implications for precision medicine and drug development for many intractable diseases.

The medical field is an important application direction of artificial intelligence. Unlike the Internet, the transformation of artificial intelligence in the medical field is subversive , the past five years have been an accelerated period of artificial intelligence medical development, and artificial intelligence has been widely used in the medical and health field. What are the main application scenarios of artificial intelligence in medical care?

1. Smart drug development

Intelligent drug research and development refers to the application of deep learning technology in artificial intelligence to drug research, through big data analysis and other technical means to quickly , Accurately excavate and screen out suitable compounds or organisms, so as to shorten the research and development cycle of new drugs, reduce the cost of new drug research and development, and improve the success rate of new drug research and development.

New drug development is a long, time-consuming and risky process. The Center for Drug Research and Development at Tufts University found through data on previously approved drugs that it takes at least 10 years and a huge investment of $2.6 billion to develop a new drug. Artificial intelligence technology can play a very important role in the development of new drugs.

Dr. Alex Zhavoronkov, founder and CEO of Insilicon, an artificial intelligence drug research and development company, previously stated that compared with the traditional research and development model , artificial intelligence can not only accelerate the development of new drugs, but also improve the success rate of drug research and development, pharmaceutical companies can enjoy a longer post-market patent protection period, and more importantly, the developed drugs will be cheaper.

2. Intelligent diagnosis and treatment

What is Smart Care? It is to apply artificial intelligence to medical diagnosis and treatment, let the machine "learn" the medical experience and medical literature knowledge of expert doctors, simulate the thinking logic of diagnosis and treatment, and give a plan in practical application. Now, the concept of intelligent diagnosis and treatment has been further expanded, and some preparations for diagnosis and treatment can also be undertaken by machines, further reducing the pressure on doctors.

Intelligent diagnosis and treatment runs through the doctor's face-to-face consultation De qián zhōng hòu zhěnggè liúchéng, mùqián zhǔliú de kāifā fāngxiàng bāokuò: Yǔyīn bìnglì, fǔzhù juécè, fēngxiǎn yùjǐng děng lǐngyù. Bǐrú zhìnéng yǔyīn bìnglì, jiùshì tōngguò yǔyīn shìbié jìshù, bāngzhù yīshēng kuàisù lùrù bìnglì, dé xìn shùjù xiǎnshì, zhōngguó 50%yǐshàng de zhùyuàn yīshēng píngjūn měitiān yǒu 4 xiǎoshí yǐshàng zài xiě bìnglì, ér yìngyòng yǔyīn bìnglì hòu, yīshēng de zhǔsù nèiróng kěyǐ shíshí dì zhuàn huàn chéng wénzì, xiàolǜ dàdà tíshēng.

zài bǐrú fǔzhù zhìliáo juécè, fǔzhù zhìliáo juécè shì hěnduō kējì gōngsī mùqián zhòngdiǎn yánjiū de fāngxiàng, tōngguò xiānjìn suànfǎ, yǐ línchuáng zhǐnán zhīshì kù wèi jīchǔ, jiéhé yīshēng jīngyàn, duì hǎiliàng zhēnshí de línchuáng zhěnliáo shùjù hé lí yuàn suífǎng shùjù jìnxíng xùnliàn, nénggòu wājué zhìliáo fāng'àn hé jiéjú de guānlián, duìbǐ bùtóng zhìliáo fāng'àn de xiàoguǒ. Cóng'ér xiézhù yīshēng wéi huànzhě tígōng gèng jīngzhǔn yōuzhì de zhěnliáo fāng'àn.

3, yīxué yǐngxiàng zhìnéng shìbié

AI yīxué yǐngxiàng shì zhǐ lìyòng AI zài gǎnjué rèn zhī hé shēndù xuéxí de jìshù yōushì, jiāng qí yìngyòng zài yīxué yǐngxiàng lǐngyù, shíxiàn jīqì duì yīxué yǐngxiàng de fēnxī pànduàn, shì xiézhù yīshēng wánchéng zhěnduàn, zhìliáo gōngzuò de yī zhǒng fǔzhù gōngjù, bāngzhù yīshēng gèng kuài huòqǔ yǐngxiàng xìnxī, jìnxíng dìngliàng fēnxī, tíshēng yīshēng kàn tú, dú tú de xiàolǜ, xiézhù fāxiàn yǐncáng bìngzào, cóng'ér dádào tígāo zhěnduàn xiàolǜ hé zhǔnquè lǜ de mùdì.

réngōng zhìnéng zài yīxué yǐngxiàng yìngyòng zhǔyào fēn wéi liǎng bùfèn: Yī shì túxiàng shìbié, yìngyòng yú gǎnzhī huánjié, qí zhǔyào mùdì shì jiāng yǐngxiàng jìn háng fēnxī, huòqǔ yīxiē yǒu yìyì de xìnxī; èr shì shēndù xuéxí, yìngyòng yú xuéxí hé fēnxī huánjié, tōng guo dàliàng de yǐngxiàng shùjù hé zhěnduàn shùjù, bùduàn duì shénjīng yuán wǎngluò jìnxíng shēndù xuéxí xùnliàn, cùshǐ qí zhǎngwò zhěnduàn nénglì.

4, yīliáo jīqìrén

yīliáo jīqìrén shì yī zhǒng zhìnéng xíng fúwù jīqìrén, tā jùyǒu guǎngfàn de gǎnjué xìtǒng , zhìnéng hé jīngmì zhíxíng jīgòu, cóngshì yīliáo huò fǔzhù yīliáo gōngzuò. Yīliáo jīqìrén de mùdì bìng bùshì dàitì shǒushù yīshēng, ér shì zuòwéi yī zhǒng fǔzhù gōngjù lái tàzhǎn yīshēng de shǒushù nénglì, tígāo shǒushù zhìliàng, jiǎnqīng yīshēng de gōngzuò qiángdù.

yīliáo jīqìrén jùyǒu jiàowéi guǎngfàn de gàiniàn, bāokuò wàikē shǒushù jīqìrén, kāngfù jīqìrén, yīliáo fúwù jīqìrén hé wéixíng jiǎncè yǔ zhìliáo jīqìrén děng. Wàikē shǒushù jīqìrén gēnjù shǒushù lèixíng bùtóng kě fēn wéi xiǎn wéi wàikē shǒushù jīqìrén, shénjīng wàikē shǒushù jīqìrén, ěrbí hóu wàiké shǒushù jīqìrén, zhěngxíng wàikē yǔ gǔkē shǒushù jīqìrén děng.

jìnnián lái, wǒguó míngquè tíchū yào fāzhǎn “yīyòng jīqìrén děng gāo xìngnéng zhěnliáo shèbèi”, yīliáo fúwù jīqìrén chéngxiàn kuàisù zēngzhǎng tàishì. Shùjù xiǎnshì,2020 nián wǒguó yīliáo fúwù jīqìrén shìchǎng guīmó dá 59.4 Yì yuán, yùjì 2022 nián zhōngguó yīliáo jīqìrén jiāng jìnyībù dádào 97.1 Yì yuán.

5, zhìnéng jiànkāng guǎnlǐ

gēnjù réngōng zhìnéng ér jiànzào de zhìnéng shèbèi kěyǐ jiāncè dào rénmen de yīxiē jīběn shēntǐ tèzhēng, rú yǐnshí, shēntǐ jiànkāng zhǐshù, shuìmián děng, duì shēntǐ sùzhì jìnxíng pínggū, tígōng gèxìng de jiànkāng guǎnlǐ fāng'àn, jíshí shìbié jíbìng fāshēng de fēngxiǎn, tíxǐng yònghù zhùyì zìjǐ de shēntǐ jiànkāng ānquán. Mùqián réngōng zhìnéng zài jiànkāng guǎnlǐ fāngmiàn de yìngyòng zhǔyào zài fēngxiǎn shìbié, xūnǐ hùshì, jīngshén jiànkāng, zàixiàn wèn zhěn, jiànkāng gānyù yǐjí jīyú jīngzhǔn yīxué de jiànkāng guǎnlǐ.

jiànkāng guǎnlǐ hángyè yīn qí yùfáng, tiáoyǎng de jī tiáo hé gètǐ huà guǎnlǐ de tèxìng, zhèngzài chéngwéi yùfáng yīxué de zhǔliú.“Shísìwǔ” qíjiān wǒguó jìnrù gāo zhìliàng fāzhǎn de xīn jiēduàn, wǒguó jiànkāng guǎnlǐ yě jiāng jìnrù yīgè xīn de fǎ zhǎn jiēduàn. Miànlín jīyù hé tiǎozhàn, jiànkāng guǎnlǐ fúwù jiāng xiàngzhe gèngjiā guǎngfàn, shēnrù hé gèxìng huà zhuǎnbiàn, lìyòng AI jìshù duì jiànkāng guǎnlǐ jìnxíng zhìnéng shēngjí de zhìnéng jiànkāng guǎnlǐ shì mùqián shìhé wǒguó guóqíng de yī zhǒng jiànkāng guǎnlǐ fāngshì.

xiǎojié

Another example is adjuvant therapy decision-making. Adjuvant therapy decision-making is the current focus of many technology companies. Through advanced algorithms, clinical guidelines Based on the knowledge base, combined with the experience of doctors, training on massive real clinical diagnosis and treatment data and discharge follow-up data can mine the correlation between treatment plans and outcomes, and compare the effects of different treatment plans. This will help doctors to provide more accurate and high-quality diagnosis and treatment plans for patients.

3. Intelligent recognition of medical images

AI medical imaging refers to using AI's technical advantages in sensory cognition and deep learning to apply it in the field of medical imaging, The realization of the machine's analysis and judgment of medical images is an auxiliary tool to assist doctors in completing diagnosis and treatment. It helps doctors to obtain image information faster, conduct quantitative analysis, improve the efficiency of doctors' viewing and reading of images, and assist in discovering hidden lesions. So as to achieve the purpose of improving the diagnostic efficiency and accuracy.

The application of artificial intelligence in medical imaging is mainly divided into two parts: one is image recognition, which is applied to the perception link. Its main purpose is to Analyze the image to obtain some meaningful information; the second is deep learning, which is applied to the learning and analysis process. Through a large amount of image data and diagnostic data, the neuron network is continuously trained in deep learning to enable it to master the diagnostic ability.

4. Medical robot

Medical Robotis an intelligent service robot with an extensivesensation system , smart and precision actuators for medical or paramedical work. The purpose of medical robots is not to replace the surgeon, but as an auxiliary tool to expand the surgeon's surgical ability, improve the quality of surgery, and reduce the doctor's work intensity.

Medical robots have a wide range of concepts, including surgical robots, rehabilitation robots, medical service robots, and micro-detection and treatment robots. . Surgical robots can be divided into microsurgery robots, neurosurgery robots, ENT shell surgical robots, plastic surgery and orthopaedic surgical robots, etc.

In recent years, my country has clearly proposed to develop "high-performance diagnostic equipment such as medical robots", and medical service robots have shown a rapid growth trend. Data show that in 2020, the scale of my country's medical service robot market will reach 5.94 billion yuan, and it is expected that China's medical robots will further reach 9.71 billion yuan in 2022.

5. Intelligent health management

Smart devices built with artificial intelligence can monitor some basic physical characteristics of people, such as diet, body health index, sleep Etc., evaluate physical fitness, provide personalized health management plans, identify the risk of disease in time, and remind users to pay attention to their own health and safety. At present, the application of artificial intelligence in health management is mainly in risk identification, virtual nurses, mental health, online consultation, health intervention and health management based on precision medicine.

The health management industry is becoming the mainstream of preventive medicine because of its prevention, nursing tone and individualized management characteristics. During the "14th Five-Year Plan" period, my country has entered a new stage of high-quality development, and my country's health management will also enter a new stage of development. Faced with opportunities and challenges, health management services will become more extensive, in-depth and personalized. Intelligent health management that uses AI technology to intelligently upgrade health management is a health management method that is currently suitable for my country's national conditions.

Summary