Results 81 to 90 of about 2,756,498 (272)
Interpretable Deep Convolutional Neural Networks via Meta-learning [PDF]
arXiv, 2018 Model interpretability is a requirement in many applications in which crucial decisions are made by users relying on a model's outputs. The recent movement for "algorithmic fairness" also stipulates explainability, and therefore interpretability of learning models.
arxiv
Impact of Accuracy on Model Interpretations [PDF]
arXiv, 2020 Model interpretations are often used in practice to extract real world insights from machine learning models. These interpretations have a wide range of applications; they can be presented as business recommendations or used to evaluate model bias. It is vital for a data scientist to choose trustworthy interpretations to drive real world impact.
arxiv
Molecular Oncology, EarlyView.Consensus molecular subtypes (CMS1‐4) have been identified to study colorectal cancer heterogeneity and serve as potential biomarkers. In this study, we developed and evaluated NanoCMSer, a NanoString‐based classifier using 55 genes, optimized for FF and FFPE to facilitate the clinical evaluation of CMS subtyping.
Arezo Torang +10 more
wiley +1 more source
Common pitfalls in statistical analysis: Clinical versus statistical significance
Perspectives in Clinical Research, 2015 In clinical research, study results, which are statistically significant are often interpreted as being clinically important. While statistical significance indicates the reliability of the study results, clinical significance reflects its impact on ...
Priya Ranganathan +2 more
doaj +1 more source
Molecular Oncology, EarlyView.Tumor microenvironment drives cancer formation and progression. We analyzed the role of human cancer‐associated adipocytes from patients with renal cell carcinoma (RCC) stratified as lean, overweight, or obese. RNA‐seq demonstrated that, among the most altered genes involved in the tumor–stroma crosstalk, are ADAM12 and CYP1B1, which were proven to be ...
Sepehr Torabinejad +13 more
wiley +1 more source
Molecular Oncology, EarlyView.Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran +16 more
wiley +1 more source
Molecular Oncology, EarlyView.The authors conducted a retrospective study of 94 patients with advanced cancer who underwent next‐generation sequencing (NGS) gene panel analysis and received targeted treatments when applicable. Results further support evidence indicating that molecular profiling provides clinical benefit.
Michaël Dang +3 more
wiley +1 more source
Challenges and opportunities in visual interpretation of Big Data [PDF]
arXiv, 2018 We live in a world where data generation is omnipresent. Innovations in computer hardware in the last few decades coupled with increasingly reliable connectivity among them have fueled this phenomenon. We are constantly creating and consuming data across digital devices of varying form factors.
arxiv
Molecular Oncology, EarlyView.Transient receptor potential melastatin‐4 (TRPM4) is overexpressed in prostate cancer (PCa). Knockout of TRPM4 resulted in reduced PCa tumor spheroid size and decreased PCa tumor spheroid outgrowth. In addition, lack of TRPM4 increased cell death in PCa tumor spheroids.
Florian Bochen +6 more
wiley +1 more source