Bioterrorism

In response to 'The clinical artificial intelligence department: a prerequisite for success'.

A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT.

Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine a...

A Randomized Controlled Trial of an Intelligent Robotic Response to Joint Attention Intervention System.

Although there has been growing interest in utilizing robots for intervention in autism spectrum dis...

Novel Feature Selection for Artificial Intelligence Using Item Response Theory for Mortality Prediction.

Feature selection is a critical component in supervised machine learning classification analyses. Ex...

Frequency-dependent response in cortical network with periodic electrical stimulation.

Electrical stimulation can shape oscillations in brain activity. However, the mechanism of how perio...

Artificial Intelligence: A Singapore Response.

Detecting Patient Deterioration Using Artificial Intelligence in a Rapid Response System.

OBJECTIVES: As the performance of a conventional track and trigger system in a rapid response system...

Machine learning-guided intervention trials to predict treatment response at an individual patient level: an important second step following randomized clinical trials.

Response to Chelli and Boileau: "Let's 'recall' sensitivity and specificity".

Ultra-gentle soft robotic fingers induce minimal transcriptomic response in a fragile marine animal.

Tessler et al. demonstrate that a 'soft' robot causes less stress to a jellyfish while handling comp...

Machine learning-based prediction of response to growth hormone treatment in Turner syndrome: the LG Growth Study.

Background Growth hormone (GH) treatment has become a common practice in Turner syndrome (TS). Howev...

Assessing the Risks Posed by the Convergence of Artificial Intelligence and Biotechnology.

Rapid developments are currently taking place in the fields of artificial intelligence (AI) and biot...

Author response to: Comment on: Bioethical approach to robot-assisted surgery.

ReSimNet: drug response similarity prediction using Siamese neural networks.

MOTIVATION: Traditional drug discovery approaches identify a target for a disease and find a compoun...

A Deep Learning Framework for Predicting Response to Therapy in Cancer.

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

Response to Comment on "Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission".

On the promise of artificial intelligence for standardizing radiographic response assessment in gliomas.

Author response to: Comment on: Bioethical approach to robot-assisted surgery in the era of shared decision making.

Development and Validation of a Machine Learning Algorithm for Predicting Response to Anticholinergic Medications for Overactive Bladder Syndrome.

OBJECTIVE: To develop and externally validate a prediction model for anticholinergic response in pat...

Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.

We hypothesize that convolutional neural networks (CNN) can be used to predict neoadjuvant chemother...

Integration of machine learning and pharmacogenomic biomarkers for predicting response to antidepressant treatment: can computational intelligence be used to augment clinical assessments?