Bioterrorism

Modelling and Optimizing Pyrene Removal from the Soil by Phytoremediation using Response Surface Methodology, Artificial Neural Networks, and Genetic Algorithm.

This study aimed to model and optimize pyrene removal from the soil contaminated by sorghum bicolor ...

Machine learning and data mining frameworks for predicting drug response in cancer: An overview and a novel in silico screening process based on association rule mining.

A major challenge in cancer treatment is predicting the clinical response to anti-cancer drugs on a ...

Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response.

BACKGROUND: Identification of functional non-coding variants and their mechanistic interpretation is...

Supplementation of OmniGen-AF improves the metabolic response to a glucose tolerance test in beef heifers.

This study determined whether feeding the immunomodulating supplement, OmniGen-AF, to feedlot heifer...

Extraction and optimization of exopolysaccharide from sp. using response surface methodology and artificial neural networks.

The microbial polysaccharides secreted and produced from various microbes into their extracellular e...

Improving prediction of phenotypic drug response on cancer cell lines using deep convolutional network.

BACKGROUND: Understanding the phenotypic drug response on cancer cell lines plays a vital role in an...

On how to not misuse hierarchical clustering on principal components to define clinically meaningful patient subgroups. Response to: 'On using machine learning algorithms to define clinical meaningful patient subgroups' by Pinal-Fernandez and Mammen.

Modeling azo dye removal by sono-fenton processes using response surface methodology and artificial neural network approaches.

Textile industry wastewaters, which cause serious problems in the environment and human health, incl...

Response to repeat echoendoscopic celiac plexus neurolysis in pancreatic cancer patients: A machine learning approach.

BACKGROUND: /Objectives: Efficacy of repeat echoendoscopic celiac plexus neurolysis is still unclear...

Prediction of Chemotherapy Response of Osteosarcoma Using Baseline F-FDG Textural Features Machine Learning Approaches with PCA.

PURPOSE: Patients with high-grade osteosarcoma undergo several chemotherapy cycles before surgical i...

Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging.

BACKGROUND: We attempted to train and validate a model of deep learning for the preoperative predict...

Incorporating Laboratory Values Into a Machine Learning Model Improves In-Hospital Mortality Predictions After Rapid Response Team Call.

OBJECTIVES: Machine learning models have been used to predict mortality among patients requiring rap...

Envisioning the expertise of the future.

Envisioning the expertise of the future in the field of food safety is challenging, as society, scie...

Handcrafted versus deep learning radiomics for prediction of cancer therapy response.

mSphere of Influence: the Rise of Artificial Intelligence in Infection Biology.

Artur Yakimovich works in the field of computational virology and applies machine learning algorithm...

MR-based artificial intelligence model to assess response to therapy in locally advanced rectal cancer.

PURPOSE: To develop and validate an Artificial Intelligence (AI) model based on texture analysis of ...

Machine Learning Prediction of Response to Cardiac Resynchronization Therapy: Improvement Versus Current Guidelines.

BACKGROUND: Cardiac resynchronization therapy (CRT) has significant nonresponse rates. We assessed w...

Response to Letter to the Editor on "Robot-Assisted Total Knee Arthroplasty Does Not Improve Long-Term Clinical and Radiologic Outcomes".

Response to Editorial "Artificial intelligence, machine learning, and the human interface in medicine: Is there a sweet spot for oral and maxillofacial radiology?".

Response to Letters to the Editor regarding the editorial "Artificial intelligence, machine learning, and the human interface in medicine: is there a sweet spot for oral and maxillofacial radiology?".

One-lung ventilation duration-dependent stress response in thoracotomies and the effect of a low-volume, high-frequency differentiated ventilation strategy on this response.

BACKGROUND: This study aims to investigate the effect of ventilation of the non-ventilated lung in p...