The rapidly emerging field of computational pathology has demonstrated promise in developing objective prognostic models from histology images. However, most prognostic models are either based on histology or genomics alone and do not address how the...
Meaningful integration of artificial intelligence (AI) will transform the application of "big data" for patient care, diagnosis, and research. In this issue of Cancer Cell, Chen et al. describe a transparent system to integrate histopathology and mol...
A novel machine learning approach predicts the impact of tumor mutations on cellular phenotypes, overcomes limited training data, minimizes costly functional validation, and advances efforts to implement cancer precision medicine.
PURPOSE: Robotic head and neck surgery is widespread nowadays. However, in the reconstruction field, the use of robotic operations is not. This article aimed to examine methodologies for conventional head and neck reconstruction after robotic tumor s...
Discovering rare cancer driver genes is difficult because their mutational frequency is too low for statistical detection by computational methods. EPIMUTESTR is an integrative nearest-neighbor machine learning algorithm that identifies such marginal...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Whole Slide Images (WSIs) in digital pathology are used to diagnose cancer subtypes. The difference in procedures to acquire WSIs at various trial sites gives rise to variability in the histopathology images, thus making consistent diagnosis challeng...
PURPOSE: The advancement of natural language processing (NLP) has promoted the use of detailed textual data in electronic health records (EHRs) to support cancer research and to facilitate patient care. In this review, we aim to assess EHR for cancer...
Studies in health technology and informatics
Jun 29, 2022
The accelerating impact of genomic data in clinical decision-making has generated a paradigm shift from treatment based on the anatomic origin of the tumor to the incorporation of key genomic features to guide therapy. Assessing the clinical validity...
The recent, rapid advances in immuno-oncology have revolutionized cancer treatment and spurred further research into tumor biology. Yet, cancer patients respond variably to immunotherapy despite mounting evidence to support its efficacy. Current meth...
Artificial intelligence (AI) and machine learning (ML) technologies have not only tremendous potential to augment clinical decision-making and enhance quality care and precision medicine efforts, but also the potential to worsen existing health dispa...
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