AIMC Topic: Colonic Neoplasms

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Training with Small Medical Data: Robust Bayesian Neural Networks for Colon Cancer Overall Survival Prediction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fast and accurate cancer prognosis stratification models are essential for treatment designs. Large labeled patient data can power advanced deep learning models to obtain precise predictions. However, since fully labeled patient data are hard to acqu...

Prediction of clinically actionable genetic alterations from colorectal cancer histopathology images using deep learning.

World journal of gastroenterology
BACKGROUND: Identifying genetic mutations in cancer patients have been increasingly important because distinctive mutational patterns can be very informative to determine the optimal therapeutic strategy. Recent studies have shown that deep learning-...

[A Case of Two Curative Resections for the Peritoneal Dissemination of Transverse Colon Cancer].

Gan to kagaku ryoho. Cancer & chemotherapy
No large clinical trials have been conducted to prove the efficacy of peritoneal dissemination resection for colorectal cancer, and no evidence has shown the usefulness of resection for metachronous peritoneal dissemination. An elderly woman in her 7...

An FP's guide to AI-enabled clinical decision support.

The Journal of family practice
To better understand the capabilities and challenges of artificial intelligence and machine learning, we look at the role they can play in screening for retinopathy and colon cancer.

Fuzzy Gaussian Lasso clustering with application to cancer data.

Mathematical biosciences and engineering : MBE
Recently, Yang et al. (2019) proposed a fuzzy model-based Gaussian (F-MB-Gauss) clustering that combines a model-based Gaussian with fuzzy membership functions for clustering. In this paper, we further consider the F-MB-Gauss clustering with the leas...

Effect of normalization methods on the performance of supervised learning algorithms applied to HTSeq-FPKM-UQ data sets: 7SK RNA expression as a predictor of survival in patients with colon adenocarcinoma.

Briefings in bioinformatics
MOTIVATION: One of the main challenges in machine learning (ML) is choosing an appropriate normalization method. Here, we examine the effect of various normalization methods on analyzing FPKM upper quartile (FPKM-UQ) RNA sequencing data sets. We coll...

Feature specific quantile normalization enables cross-platform classification of molecular subtypes using gene expression data.

Bioinformatics (Oxford, England)
MOTIVATION: Molecular subtypes of cancers and autoimmune disease, defined by transcriptomic profiling, have provided insight into disease pathogenesis, molecular heterogeneity and therapeutic responses. However, technical biases inherent to different...

Short-term outcomes in patients with colon cancer treated with robotic right colectomy.

Journal of B.U.ON. : official journal of the Balkan Union of Oncology
PURPOSE: To report a single surgeon series of consecutive robotic right colectomies (RRC) performed for non-metastatic right colon cancer.