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Development and validation of an endoscopic images-based deep learning model for detection with nasopharyngeal malignancies.

Cancer communications (London, England)
BACKGROUND: Due to the occult anatomic location of the nasopharynx and frequent presence of adenoid hyperplasia, the positive rate for malignancy identification during biopsy is low, thus leading to delayed or missed diagnosis for nasopharyngeal mali...

Prediction of methionine oxidation risk in monoclonal antibodies using a machine learning method.

mAbs
Monoclonal antibodies (mAbs) have become a major class of protein therapeutics that target a spectrum of diseases ranging from cancers to infectious diseases. Similar to any protein molecule, mAbs are susceptible to chemical modifications during the ...

Identify and monitor clinical variation using machine intelligence: a pilot in colorectal surgery.

Journal of clinical monitoring and computing
Standardized clinical pathways are useful tool to reduce variation in clinical management and may improve quality of care. However the evidence supporting a specific clinical pathway for a patient or patient population is often imperfect limiting ado...

Automatic Age Estimation and Majority Age Classification From Multi-Factorial MRI Data.

IEEE journal of biomedical and health informatics
Age estimation from radiologic data is an important topic both in clinical medicine as well as in forensic applications, where it is used to assess unknown chronological age or to discriminate minors from adults. In this paper, we propose an automati...

Joint Weakly and Semi-Supervised Deep Learning for Localization and Classification of Masses in Breast Ultrasound Images.

IEEE transactions on medical imaging
We propose a framework for localization and classification of masses in breast ultrasound images. We have experimentally found that training convolutional neural network-based mass detectors with large, weakly annotated datasets presents a non-trivia...

Data Curation can Improve the Prediction Accuracy of Metabolic Intrinsic Clearance.

Molecular informatics
A key consideration at the screening stages of drug discovery is in vitro metabolic stability, often measured in human liver microsomes. Computational prediction models can be built using a large quantity of experimental data available from public da...

Second branchial cleft anomalies in children: a literature review.

Pediatric surgery international
Branchial cleft anomalies are the second most common head and neck congenital lesions in children. It may sometimes be a part of branchio-oto-renal (BOR) syndrome, so in patients with branchial cleft anomalies associated with a complaint of auricular...

A universal SNP and small-indel variant caller using deep neural networks.

Nature biotechnology
Despite rapid advances in sequencing technologies, accurately calling genetic variants present in an individual genome from billions of short, errorful sequence reads remains challenging. Here we show that a deep convolutional neural network can call...

SiRNA silencing efficacy prediction based on a deep architecture.

BMC genomics
BACKGROUND: Small interfering RNA (siRNA) can be used to post-transcriptional gene regulation by knocking down targeted genes. In functional genomics, biomedical research and cancer therapeutics, siRNA design is a critical research topic. Various com...

Deep learning-based transcriptome data classification for drug-target interaction prediction.

BMC genomics
BACKGROUND: The ability to predict the interaction of drugs with target proteins is essential to research and development of drug. However, the traditional experimental paradigm is costly, and previous in silico prediction paradigms have been impeded...