Bioterrorism

Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization.

Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-s...

A baseline model including quantitative anti-HBc to predict response of peginterferon in HBeAg-positive chronic hepatitis B patients.

BACKGROUND: Few models to predict antiviral response of peginterferon were used in hepatitis B e ant...

Function of a multimodal signal: A multiple hypothesis test using a robot frog.

Multimodal communication may evolve because different signals may convey information about the signa...

Identification of stress response proteins through fusion of machine learning models and statistical paradigms.

Proteins are a vital component of cells that perform physiological functions to ensure smooth operat...

Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-ch...

Machine Learning-Based Single Cell and Integrative Analysis Reveals That Baseline mDC Predisposition Correlates With Hepatitis B Vaccine Antibody Response.

Vaccination to prevent infectious disease is one of the most successful public health interventions ...

Using predictive machine learning models for drug response simulation by calibrating patient-specific pathway signatures.

The utility of pathway signatures lies in their capability to determine whether a specific pathway o...

Reinforcing bar development length modeling using integrative support vector regression model with response surface method: New approach.

Due to the non-uniformity of bond stress distribution, the full bar development length should be tes...

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study.

BACKGROUND: Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast duri...

Public Perception and Reception of Robotic Applications in Public Health Emergencies Based on a Questionnaire Survey Conducted during COVID-19.

Various intelligent technologies have been applied during COVID-19, which has become a worldwide pub...

Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study.

OBJECTIVES: Breast cancer (BC) is the most common cancer in women worldwide, and neoadjuvant chemoth...

Rise of the Machines? Predicting Brivaracetam Response Using Machine Learning.

Advanced robotics as a support in healthcare organizational response: A COVID-19 pandemic case study.

The use of robotics is becoming widespread in healthcare. However, little is known about how robotic...

Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy.

Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and ide...

Structural Response Prediction for Damage Identification Using Wavelet Spectra in Convolutional Neural Network.

If damage to a building caused by an earthquake is not detected immediately, the opportunity to deci...

The use of deep learning on endoscopic images to assess the response of rectal cancer after chemoradiation.

BACKGROUND: Accurate response evaluation is necessary to select complete responders (CRs) for a watc...

Systemic inflammatory response in robot-assisted and laparoscopic surgery for colon cancer (SIRIRALS): study protocol of a randomized controlled trial.

BACKGROUND: Robot-assisted surgery is being increasingly adopted in treating colorectal cancer, and ...

Sensorless Estimation Based on Neural Networks Trained with the Dynamic Response Points.

In the present work, a neuronal dynamic response prediction system is shown to estimate the response...

Cutoff criteria for the placebo response: a cluster and machine learning analysis of placebo analgesia.

Computations of placebo effects are essential in randomized controlled trials (RCTs) for separating ...

Multimodal deep learning models for the prediction of pathologic response to neoadjuvant chemotherapy in breast cancer.

The achievement of the pathologic complete response (pCR) has been considered a metric for the succe...

Ten public health strategies to control the Covid-19 pandemic: the Saudi Experience.

Saudi Arabia plays an important strategic role within the Middle East and afar because of its geogra...