Mitochondrion, a tiny energy factory, plays an important role in various biological processes of most eukaryotic cells. Mitochondrial defection is associated with a series of human diseases. Knowledge of the submitochondrial locations of proteins can...
IEEE journal of biomedical and health informatics
Oct 8, 2014
The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, li...
Guided by Fuzzy Trace Theory, this study examined the impact of a 'Gist-based' leaflet on colorectal cancer screening knowledge and intentions; and tested the interaction with participants' numerical ability. Adults aged 45-59 years from four UK gene...
Statistical methods in medical research
Sep 18, 2013
BACKGROUND: Recent literature on the comparison of machine learning methods has raised questions about the neutrality, unbiasedness and utility of many comparative studies. Reporting of results on favourable datasets and sampling error in the estimat...
The immune microenvironment is a crucial component of colorectal carcinoma that has been well characterized, but much less is known about the immune microenvironment of colorectal carcinoma precursors. We hypothesized that T-cell infiltrates might di...
UNLABELLED: Dysregulation of the tumor suppressor gene adenomatous polyposis coli (APC) is a canonical step in colorectal cancer development by promoting activation of the WNT/β-catenin pathway. Curiously, most colorectal tumors carry biallelic mutat...
BACKGROUND: Deep learning (DL) models are effective pre-screening tools for detecting mismatch repair deficiency (dMMR) in colorectal carcinoma (CRC). These models have been trained and validated on large cohorts from the Northern Hemisphere, without...
OBJECTIVES: Benign lymph node enlargement can mislead surgeons into overstaging colorectal cancer (CRC), causing unnecessarily extended lymphadenectomy. This study aimed to develop and validate a machine learning (ML) classifier utilizing multi-phase...
UNLABELLED: Recent studies have reported increases in early-onset cancer cases (diagnosed less than 50 years of age) and raised questions about whether the increase is related to earlier diagnosis from nonspecific medical tests as reflected by decrea...
PURPOSE: The aim of this study was to develop and validate CT venous phase image-based radiomics to predict BRAF gene mutation status in preoperative colorectal cancer patients.
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