High-performance medicine: the convergence of human and artificial intelligence

EJ Topol - Nature medicine, 2019 - nature.com
The use of artificial intelligence, and the deep-learning subtype in particular, has been
enabled by the use of labeled big data, along with markedly enhanced computing power …

Resolving genetic heterogeneity in cancer

S Turajlic, A Sottoriva, T Graham… - Nature Reviews Genetics, 2019 - nature.com
To a large extent, cancer conforms to evolutionary rules defined by the rates at which clones
mutate, adapt and grow. Next-generation sequencing has provided a snapshot of the …

A review of deep learning on medical image analysis

J Wang, H Zhu, SH Wang, YD Zhang - Mobile Networks and Applications, 2021 - Springer
Compared with common deep learning methods (eg, convolutional neural networks),
transfer learning is characterized by simplicity, efficiency and its low training cost, breaking …

[HTML][HTML] Translating cancer genomics into precision medicine with artificial intelligence: applications, challenges and future perspectives

J Xu, P Yang, S Xue, B Sharma, M Sanchez-Martin… - Human genetics, 2019 - Springer
In the field of cancer genomics, the broad availability of genetic information offered by next-
generation sequencing technologies and rapid growth in biomedical publication has led to …

[HTML][HTML] Clonal architecture in mesothelioma is prognostic and shapes the tumour microenvironment

M Zhang, JL Luo, Q Sun, J Harber, AG Dawson… - Nature …, 2021 - nature.com
Abstract Malignant Pleural Mesothelioma (MPM) is typically diagnosed 20–50 years after
exposure to asbestos and evolves along an unknown evolutionary trajectory. To elucidate …

Subclonal reconstruction of tumors by using machine learning and population genetics

G Caravagna, T Heide, MJ Williams, L Zapata… - Nature …, 2020 - nature.com
Most cancer genomic data are generated from bulk samples composed of mixtures of cancer
subpopulations, as well as normal cells. Subclonal reconstruction methods based on …

[HTML][HTML] Normal tissue architecture determines the evolutionary course of cancer

J West, RO Schenck, C Gatenbee… - Nature …, 2021 - nature.com
Cancer growth can be described as a caricature of the renewal process of the tissue of
origin, where the tissue architecture has a strong influence on the evolutionary dynamics …

Integrating artificial and human intelligence: a partnership for responsible innovation in biomedical engineering and medicine

K Dzobo, S Adotey, NE Thomford… - Omics: a journal of …, 2020 - liebertpub.com
Historically, the term “artificial intelligence” dates to 1956 when it was first used in a
conference at Dartmouth College in the US. Since then, the development of artificial …

[HTML][HTML] Tumor heterogeneity: preclinical models, emerging technologies, and future applications

M Proietto, M Crippa, C Damiani, V Pasquale… - Frontiers in …, 2023 - frontiersin.org
Heterogeneity describes the differences among the cancer cells within and between tumors.
It refers to cancer cells describing variations in morphology, transcriptional profiles …

[HTML][HTML] Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures

LS Hu, F D'Angelo, TM Weiskittel, FP Caruso… - Nature …, 2023 - nature.com
Sampling restrictions have hindered the comprehensive study of invasive non-enhancing
(NE) high-grade glioma (HGG) cell populations driving tumor progression. Here, we present …