Medical artificial intelligence: new technology brings a new era

In today's technological torrent, artificial intelligence is reshaping social development and lifestyles in unprecedented ways. As the technological revolution continues to deepen, medical artificial intelligence continues to show its unique charm and potential, becoming a key force in promoting reforms in the medical field. It can not only improve the quality of medical services, optimize disease diagnosis and treatment models, but also promote the development of the medical field towards personalization and precision. This not only means an improvement in treatment efficiency, but also a profound practice of the "patient-centered" concept, marking the transformation of the medical model from the previous "curing diseases" to "curing people".

Here is some knowledge about the development of medical artificial intelligence.

1. Precision medicine

The application of medical artificial intelligence technology in the field of precision medicine can provide patients with more personalized and efficient treatment plans. For example, for common cancer diseases, by collecting patients' genetic information, living habits, past medical history, physiological and other data, the AI ​​system can generate a directional disease risk prediction model to predict the patient's possible disease risks and complications in advance, so as to achieve early detection and early intervention. For example, for breast cancer, the AI ​​system can predict the probability of tumor recurrence by analyzing the patient's BRCAI/2 gene mutation, family history, lifestyle and other key information, and it is also convenient for doctors to adjust treatment plans based on real-time data, improve the treatment effect and improve the patient's quality of life.

2. Auxiliary diagnosis

Medical artificial intelligence in the field of auxiliary diagnosis mainly relies on deep learning algorithms to conduct detailed analysis of massive medical imaging data, such as X-rays and CT scans. It can identify subtle abnormalities in the images, detect lung nodules, tumors, vascular lesions and other diseases, and facilitate the detection of early disease risks. For example, the common lung cancer disease used to rely on manual reading of images, but it is easy to miss tiny nodules due to fatigue and visual effects. The application of AI technology will establish an image model based on the inspection data, identify subtle changes in the lungs, and use deep learning algorithms to conduct a comprehensive analysis of the specific density, morphology, texture and other characteristics of the nodules to improve the accuracy and sensitivity of disease diagnosis.

In addition, for brain CT scans, AI can achieve 3D reconstruction and accurate measurement of brain tissue changes, which can significantly improve the efficiency of diagnosing common neurological diseases such as cerebral infarction, cerebral hemorrhage, and brain tumors. In addition, the AI ​​system supports automatic diagnosis report generation, which can reduce the doctor's review time. For example, in a breast X-ray examination, the AI ​​system will examine the lesion within seconds and make a preliminary analysis of whether it is benign or malignant. After that, the doctor will combine the detailed information later to give an accurate diagnosis result.

3. Drug development

In the past, drug development cycles were generally long and required a lot of investment. In addition, due to technical limitations, the ultimate success rate of drugs was also low. The application of AI technology can effectively improve the above problems. By collecting and analyzing biological information data such as gene sequences, protein structures, and drug-target interactions, the efficacy, toxicity, and side effects of compounds can be automatically tested, shortening the experimental cycle.

For example, AI systems can simulate the synthesis and structural changes of millions of compounds, and quickly screen potential drug-effective molecular candidates. This virtual screening method can not only reduce additional costs, but also avoid omissions and ensure the effectiveness of drug treatment. In addition, during the clinical trial stage, AI technology can provide a basis for targeted dosing plans by collecting previous patient data, simulating and analyzing the responses of different patients to drugs, reducing the number of unnecessary trials, and improving trial safety and shortening the time it takes for drugs to be marketed.

4. Health management

The impact of AI technology in the field of health management has had a fundamental impact on the way modern society interacts with health. For example, the widely used health management apps, smart bracelets, wearable health monitors, etc. can collect physiological indicators such as heart rate, sleep, exercise, blood pressure, etc. according to the patient's condition, and then build a personal health portrait. This can not only help users understand their physical health anytime and anywhere, but also discover potential disease risks. For example, for patients with poor sleep quality and difficulty falling asleep, the system will prompt them to pay attention to their mental state and stress, indicating that they may have sleep disorders, and then recommend relaxation exercises, lifestyle adjustments and other measures.

In addition, AI technology will combine epidemiological information to predict users' risks of developing common chronic diseases, such as diabetes, hypertension, cardiovascular disease, etc., and remind them to pay attention to diet and lifestyle adjustments to reduce the risk of disease and achieve a healthy life.

Conclusion: The popularization and application of new medical artificial intelligence technologies have fundamentally changed the traditional medical care model and medical technology. While achieving humanization and precision, it can assist people in making more targeted health decisions based on their own circumstances and reduce the risk of disease.

Author: Zhang Yuwei Chongqing University