Artificial intelligence (AI) has emerged as an indispensable force, propelling oncology into an era of precision medicine. AI's ability to analyze complex datasets quickly and accurately has enabled us to tailor treatments with unprecedented accuracy. By sifting through vast health records, genetic profiles, and molecular data, AI uncovers hidden patterns and connections, guiding clinicians toward optimal therapies for individual patients. We have demonstrated the power of AI in characterizing the genomic heterogeneity of melanoma. We showed that integrating genomic data with known associations between genomic variation and melanoma prognosis can facilitate the identification of genomic features most relevant to patient outcome.
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Artificial intelligence in cancer target identification and drug discovery
You YJ, Lai X, Pan Y, Zheng HR, Vera J, Liu SR, Deng SY, Zhang L.
Signal Transduction and Targeted Therapy. 2022; 7:156.
We review and discuss the history of artificial intelligence for identifying novel anticancer targets. We illustrate the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence algorithms. We showcase the applications of deep learning approaches in cancer target identification and drug discovery.
A disease network-based deep learning approach for characterizing melanoma
Lai X, Zhou JF, Wessely A, Heppt M, Maier A, Berking C, Vera J, Zhang L.
International Journal of Cancer. 2022; 150(6): 1029-1044.
We propose an approach that integrates genomics data, a disease network, and a deep learning model to classify melanoma patients for prognosis, assess the impact of genomic features on the classification, and provide interpretation to the impactful features. We demonstrate that developing deep learning models based on genomics data and disease networks can contribute to personalized prognostication and treatment decisions of melanoma patients.
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence
Vera J, Lai X, Baur A, Erdmann M, Gupta S, Guttà C, Heinzerling L, Heppt M, Kazmierczak PM, Kunz M, Lischer C, Pützer B, Rehm M, Ostalecki C, Retzlaff J, Witt S, Wolkenhauer O, Berking C.
Briefing in Bioinformatics. 2022.
Under the umbrella of systems and precision medicine, researchers integrate new biotechnologies and novel computational methods including AI to personalize therapy for melanoma patients. Here, we review and discuss the developments in the diagnosis, prognosis, and treatment of melanoma patients.
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