What new possibilities can artificial intelligence bring to cancer treatment? Listen to what the experts have to say.

"Artificial intelligence can provide doctors with more information in clinical diagnosis and treatment, more accurate judgment of the symptoms, efficacy, reduce the cycle of drug research and development, is the premise and basis for malignant tumors to achieve personalized precision treatment", recently, the Chinese Association of Cancer Association Cancer Artificial Intelligence Professional Committee was formally established, Tianjin Cancer Hospital Vice President Professor Xu Bo was elected as the first chairman of the Committee.Xu Bo,
, said the commission will work to promote the development and application of artificial intelligence in the field of oncology, promote the formation of a consensus of interdisciplinary experts in the field of artificial intelligence, and provide a platform for cooperation in building a high-level, replicable and sustainable data center.
big data fusion accelerates accurate tumor diagnosis
artificial intelligence will help clinicians more accurately diagnose and treat tumors. Xu Bo, for example, is the current combination of artificial intelligence benefits of the disease. Artificial intelligence has made some research results in the judgment of breast cancer, HER2 detection, molecular type, effect evaluation and so on.
through artificial intelligence to carry out a large amount of genomics information technical analysis, but also for doctors in the clinical process to provide more information, more accurate judgment of the symptoms, efficacy, is the breast cancer to achieve personalized precision treatment of the premise and basis.
artificial intelligence technology to help physicians grow
the development of artificial intelligence technology can better let inexperienced primary doctors quickly and accurately learn more clinical experience, but also for junior doctors to develop treatment programs to provide a more effective basis.
for example, the most common ultrasound in the oncology clinical examination program is the most commonly used method of thyroid nodule screening and evaluation. Ultrasound examination is more subjectively influenced, the difference between the operator and the clarity of the ultrasound image may directly affect the result judgment, so the level requirements of the imaging physician are higher, the individual examination time is longer.
Tianjin Medical University Cancer Hospital with more than 300,000 thyroid ultrasound images as a training set for artificial intelligence model development, with 3 independent data sets as verification, based on deep learning algorithm analysis of ultrasound images to achieve artificial intelligence diagnosis of thyroid cancer retrospective, multi-center diagnostic research, found that the model in the identification of thyroid cancer sensitivity and specificity can be comparable to more than 10 years of imaging experts with more than 10 years of experience, with fast and reproducible characteristics.
the current model system still has some limitations, can not consider too many clinical parameters, can not completely replace the artificial diagnosis of thyroid cancer, but can help enhance the ability of doctors in the diagnosis of thyroid cancer, improve the efficiency of reading tablets, avoid the errors caused by tiredness.
future development can not be separated from multi-center research
artificial intelligence has deep learning ability, can effectively improve the accuracy of doctors due to level and state, improve the homogenization level of imaging diagnosis. For example, the automatic detection and identification of lung nodule images can not only improve the efficiency and accuracy of early lung cancer diagnosis, greatly reduce the workload of clinicians, but also avoid the artificial errorcause of work stress and fatigue, to help doctors more accurately and quickly determine whether patients need medical intervention.Xu Bo,
, believes that the future development of artificial intelligence, but also rely on clinical large data centers, various oncology experts, multi-center research and clinical trials, to support the parameters of artificial intelligence and effectiveness. Because there are also large individual differences between different tumors, the application and development of artificial intelligence should start with some high-risk single disease, which is more conducive to the collection and analysis of data samples, and finally establish a high-level database of tumors with Chinese characteristics and artificial intelligence.
(Tianjin Cancer Hospital Special Correspondent Zhu Wei)
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