AIMC Topic: Neoplasms

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Validation of a Machine Learning Algorithm to Predict 180-Day Mortality for Outpatients With Cancer.

JAMA oncology
IMPORTANCE: Machine learning (ML) algorithms can identify patients with cancer at risk of short-term mortality to inform treatment and advance care planning. However, no ML mortality risk prediction algorithm has been prospectively validated in oncol...

[Application of deep learning in cancer prognosis prediction model].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In recent years, deep learning has provided a new method for cancer prognosis analysis. The literatures related to the application of deep learning in the prognosis of cancer are summarized and their advantages and disadvantages are analyzed, which c...

Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning.

Chemical Society reviews
Many problems exist within the myriad of currently employed screening and diagnostic methods. Further, an incredibly wide variety of procedures are used to identify an even greater number of diseases which exist in the world. There is a definite unme...

[Health and Medical Revolution Driven by Artificial Intelligence].

Gan to kagaku ryoho. Cancer & chemotherapy
With the development and diversification of medical care, the importance of precision medicine, which selects a suitable treatment for the individual patient from a huge number of options, is increasing. It is often difficult to explain multifactoria...

Can computers conceive the complexity of cancer to cure it? Using artificial intelligence technology in cancer modelling and drug discovery.

Mathematical biosciences and engineering : MBE
Drug discovery and the development of safe and effective therapeutics is an intricate procedure, further complicated in the context of cancer research by the inherent heterogeneity and complexity of the disease. To address the difficulties of identif...

Deep learning based prediction of reversible HAT/HDAC-specific lysine acetylation.

Briefings in bioinformatics
Protein lysine acetylation regulation is an important molecular mechanism for regulating cellular processes and plays critical physiological and pathological roles in cancers and diseases. Although massive acetylation sites have been identified throu...

Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints.

The Lancet. Digital health
Artificial intelligence (AI) is a disruptive technology that involves the use of computerised algorithms to dissect complicated data. Among the most promising clinical applications of AI is diagnostic imaging, and mounting attention is being directed...

Prediction of survival rate and effect of drugs on cancer patients with somatic mutations of genes: An AI-based approach.

Chemical biology & drug design
The causal role of somatic mutation and its interrelationship with gene expression profile during tumor development has already been observed, which plays a major role to decide the cancer grades and overall survival. Accurate and robust prediction o...

[Synergistic drug combination prediction in multi-input neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Synergistic effects of drug combinations are very important in improving drug efficacy or reducing drug toxicity. However, due to the complex mechanism of action between drugs, it is expensive to screen new drug combinations through trials. It is wel...