Bioterrorism

Response to Barry re: Learning Curves and Timing of Surgical Trials: Robotic Kidney Transplantation with Regional Hypothermia by Ahlawat et al. (From: Barry JM. J Endourolo 2018;32:1166; DOI: 1089/end.2018.0419).

Response to Johnston re: MRI Displays the Prostatic Cancer Anatomy and Improves the Bundles Management Before Robot-Assisted Radical Prostatectomy by Bianchi et al. (From: Johnston WK, III. J Endourol 2018;32:322-323).

Learning SPECT detector angular response function with neural network for accelerating Monte-Carlo simulations.

A method to speed up [Formula: see text] simulations of single photon emission computed tomography (...

Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set.

PURPOSE: To determine whether a multivariate machine learning-based model using computer-extracted f...

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma.

Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who can...

Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using FDG-PET/CT in Hodgkin and non-Hodgkin lymphomas.

BACKGROUND: 18F-FDG-PET/CT has become a standard for assessing treatment response in patients with l...

Comparison of response surface methodology and artificial neural network to optimize novel ophthalmic flexible nano-liposomes: Characterization, evaluation, in vivo pharmacokinetics and molecular dynamics simulation.

To improve the topical delivery of pilocarpine hydrochloride (PN) to treat glaucoma, flexible nano-l...

Complexity in mood disorder diagnosis: fMRI connectivity networks predicted medication-class of response in complex patients.

OBJECTIVE: This study determined the clinical utility of an fMRI classification algorithm predicting...

Correlation of Prostate Cancer CHD1 Status with Response to Androgen Deprivation Therapy: a Pilot Study.

INTRODUCTION: CHD1 has been identified as a tumor suppressor gene in prostate cancer. Previous studi...

Response to Skarecky re: Development of a Patient-Based Model for Estimating Operative Times for Robot-Assisted Radical Prostatectomy by Huben et al.

Optimization of multiplex quantitative polymerase chain reaction based on response surface methodology and an artificial neural network-genetic algorithm approach.

Multiplex quantitative polymerase chain reaction (qPCR) has found an increasing range of application...

Delta activity encodes taste information in the human brain.

The categorization of food via sensing nutrients or toxins is crucial to the survival of any organis...

Drug response prediction by ensemble learning and drug-induced gene expression signatures.

Chemotherapeutic response of cancer cells to a given compound is one of the most fundamental informa...

Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm.

OBJECTIVES: In the postneoadjuvant chemotherapy (NAC) setting, conventional radiographic complete re...

Optimization of goose breast meat tenderness by rapid ultrasound treatment using response surface methodology and artificial neural network.

The aim of this study was to develop a prediction model on tenderization of goose breast meat by res...

Optimization and modeling of methyl orange adsorption onto polyaniline nano-adsorbent through response surface methodology and differential evolution embedded neural network.

Presence of pigments and dyes in water bodies are growing tremendously and pose as toxic materials a...

Letter to the Editor (Response from author): MeSH qualifiers, publication types and relation occurrence frequency are also useful for a better sentence-level extraction of biomedical relations.

Cancer Drug Response Profile scan (CDRscan): A Deep Learning Model That Predicts Drug Effectiveness from Cancer Genomic Signature.

In the era of precision medicine, cancer therapy can be tailored to an individual patient based on t...

Fitting of dynamic recurrent neural network models to sensory stimulus-response data.

We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural netw...

Predicting lithium treatment response in bipolar patients using gender-specific gene expression biomarkers and machine learning.

We sought to test the hypothesis that transcriptome-level gene signatures are differentially expres...

Understanding the Patterns of Health Information Dissemination on Social Media during the Zika Outbreak.

Social media are important platforms for risk communication during public health crises. Effective d...