AIMC Topic: Humans
Showing 65991 to 66000 of 95995 articles
Automating the Paris System for urine cytopathology-A hybrid deep-learning and morphometric approach.
Cancer cytopathology
Jan 31, 2019
BACKGROUND: The Paris System for Urine Cytopathology (the Paris System) has succeeded in making the analysis of liquid-based urine preparations more reproducible. Any algorithm seeking to automate this system must accurately estimate the nuclear-to-c...
Argentinian multicenter study on urinary tract infections due to Streptococcus agalactiae in adult patients.
Journal of infection in developing countries
Jan 31, 2019
INTRODUCTION: Streptococcus agalactiae (group B streptococcus, GBS) is a recognized urinary pathogen both in males and pregnant or non-pregnant women. Data regarding GBS serotypes recovered from urinary tract infections (UTIs) are scarce. The aim of ...
A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.
Scientific reports
Jan 31, 2019
With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have improved, but at the cost of increased treatment plan complexity and planning time. The accurate prediction of dose distributions would alleviate thi...
Discovering highly selective and diverse PPAR-delta agonists by ligand based machine learning and structural modeling.
Scientific reports
Jan 31, 2019
PPAR-δ agonists are known to enhance fatty acid metabolism, preserving glucose and physical endurance and are suggested as candidates for treating metabolic diseases. None have reached the clinic yet. Our Machine Learning algorithm called "Iterative ...
Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages.
Scientific reports
Jan 31, 2019
High-grade gliomas are the most aggressive malignant brain tumors. Accurate pre-operative prognosis for this cohort can lead to better treatment planning. Conventional survival prediction based on clinical information is subjective and could be inacc...
Selecting precise reference normal tissue samples for cancer research using a deep learning approach.
BMC medical genomics
Jan 31, 2019
BACKGROUND: Normal tissue samples are often employed as a control for understanding disease mechanisms, however, collecting matched normal tissues from patients is difficult in many instances. In cancer research, for example, the open cancer resource...
A robust fuzzy rule based integrative feature selection strategy for gene expression data in TCGA.
BMC medical genomics
Jan 31, 2019
BACKGROUND: Lots of researches have been conducted in the selection of gene signatures that could distinguish the cancer patients from the normal. However, it is still an open question on how to extract the robust gene features.
Predicting drug response of tumors from integrated genomic profiles by deep neural networks.
BMC medical genomics
Jan 31, 2019
BACKGROUND: The study of high-throughput genomic profiles from a pharmacogenomics viewpoint has provided unprecedented insights into the oncogenic features modulating drug response. A recent study screened for the response of a thousand human cancer ...
Temporal indexing of medical entity in Chinese clinical notes.
BMC medical informatics and decision making
Jan 31, 2019
BACKGROUND: The goal of temporal indexing is to select an occurred time or time interval for each medical entity in clinical notes, so that all medical entities can be indexed on a united timeline, which could assist the understanding of clinical not...
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Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD.
BMC medical informatics and decision making
Jan 31, 2019
BACKGROUND: Disease comorbidity is very common and has significant impact on disease treatment. Revealing the associations among diseases may help to understand the mechanisms of diseases, improve the prevention and treatment of diseases, and support...
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