Bioterrorism

Early response to SPN-812 (viloxazine extended-release) can predict efficacy outcome in pediatric subjects with ADHD: a machine learning post-hoc analysis of four randomized clinical trials.

Machine learning (ML) was used to determine whether early response can predict efficacy outcome in pediatric subjects with ADHD treated with SPN-812. We used data from four Phase 3 placebo-controlled trials of 100- to 600-mg/day SPN-812 (N=1397; 6-17 years of age). The treatment response was defined as having a ≥50% reduction in change from baseline (CFB) in ADHD Rating Scale-5 (ADHD-RS-5) Total s...

Utilization of circulating cell-free DNA profiling to guide first-line chemotherapy in advanced lung squamous cell carcinoma.

Platinum-based chemotherapy is one of treatment mainstay for patients with advanced lung squamous cell carcinoma (LUSC) but it is still a "one-size fits all" approach. Here, we aimed to investigate the predictive and monitoring role of circulating cell-free DNA (cfDNA) profiling for the outcome of first-line chemotherapy in patients with advanced LUSC. Peripheral blood samples of 155 patients fr...

Deep learning-assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases.

Accurate evaluation of tumor response to preoperative chemotherapy is crucial for assigning appropriate patients with colorectal liver metastases (CRL...

How artificial intelligence may help the Covid-19 pandemic: Pitfalls and lessons for the future.

The clinical severity, rapid transmission and human losses due to coronavirus disease 2019 (Covid-19) have led the World Health Organization to declar...

Imaging Beyond Seeing: Early Prognosis of Cancer Treatment.

Assessing cancer response to therapeutic interventions has been realized as an important course to early predict curative efficacy and treatment outco...

M Lung-Sys: A Deep Learning System for Multi-Class Lung Pneumonia Screening From CT Imaging.

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preve...

Intractable airsickness associated with COVID-19: A case report.

A 29-yr-old male Melicopter co-pilot with high flight hours in air transport missions of the patients with COVID-19 tested positive for his RT-PCR due...

Reducing Response Time in Motor Imagery Using A Headband and Deep Learning.

Electroencephalography (EEG) signals to detect motor imagery have been used to help patients with low mobility. However, the regular brain computer in...

Prediction of response to cardiac resynchronization therapy using a multi-feature learning method.

We hypothesized that a multiparametric evaluation, based on the combination of electrocardiographic and echocardiographic parameters, could enhance th...

Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning.

Deep-learning (DL)-based image processing has potential to revolutionize the use of smartphones in mobile health (mHealth) diagnostics of infectious d...

Ready for the robot? A cross-sectional survey of OB/GYN fellowship directors' experience and expectations of their incoming fellow's robotic surgical skills.

To describe OB/GYN fellowship directors' (FDs) observations, expectations, and preferences of incoming fellow's robotic surgery preparedness. Cross-se...

The COVID-19 pandemic: How predictive analysis, artificial intelligence and GIS can be integrated into a clinical command system to improve disaster response and preparedness.

Country-level pandemic risk and preparedness classification based on COVID-19 data: A machine learning approach.

In this work we present a three-stage Machine Learning strategy to country-level risk classification based on countries that are reporting COVID-19 in...

Ensemble transfer learning for the prediction of anti-cancer drug response.

Transfer learning, which transfers patterns learned on a source dataset to a related target dataset for constructing prediction models, has been shown...

Digital Twin Coaching for Physical Activities: A Survey.

Digital Twin technology has been rising in popularity thanks to the popularity of machine learning in the last decade. As the life expectancy of peopl...

Knowledge gaps in immune response and immunotherapy involving nanomaterials: Databases and artificial intelligence for material design.

Exploring the interactions between the immune system and nanomaterials (NMs) is critical for designing effective and safe NMs, but large knowledge gap...

Application of an Artificial Intelligence Trilogy to Accelerate Processing of Suspected Patients With SARS-CoV-2 at a Smart Quarantine Station: Observational Study.

BACKGROUND: As the COVID-19 epidemic increases in severity, the burden of quarantine stations outside emergency departments (EDs) at hospitals is incr...

Customised Selection of the Haptic Design in C-Loop Intraocular Lenses Based on Deep Learning.

In order to increase the probability of having a successful cataract post-surgery, the customisation of the haptic design of the intraocular lens (IOL...

Viral pandemic preparedness: A pluripotent stem cell-based machine-learning platform for simulating SARS-CoV-2 infection to enable drug discovery and repurposing.

Infection with the SARS-CoV-2 virus has rapidly become a global pandemic for which we were not prepared. Several clinical trials using previously appr...

A Demonstration of Machine Learning in Detecting Frequency Following Responses in American Neonates.

In this study, we sought to evaluate the efficiencies of multiple machine learning algorithms in detecting neonates' Frequency Following Responses (FF...