Public Health & Policy

The Pitfalls of Using Open Data to Develop Deep Learning Solutions for COVID-19 Detection in Chest X-Rays.

Since the emergence of COVID-19, deep learning models have been developed to identify COVID-19 from chest X-rays. With little to no direct access to hospital data, the AI community relies heavily on public data comprising numerous data sources. Model performance results have been exceptional when training and testing on open-source data, surpassing the reported capabilities of AI in pneumonia-dete...

Deep Learning for Cancer Symptoms Monitoring on the Basis of Electronic Health Record Unstructured Clinical Notes.

PURPOSE: Symptoms are vital outcomes for cancer clinical trials, observational research, and population-level surveillance. Patient-reported outcomes (PROs) are valuable for monitoring symptoms, yet there are many challenges to collecting PROs at scale. We sought to develop, test, and externally validate a deep learning model to extract symptoms from unstructured clinical notes in the electronic h...

Survival prediction model for right-censored data based on improved composite quantile regression neural network.

With the development of the field of survival analysis, statistical inference of right-censored data is of great importance for the study of medical d...

deepHPI: a comprehensive deep learning platform for accurate prediction and visualization of host-pathogen protein-protein interactions.

Host-pathogen protein interactions (HPPIs) play vital roles in many biological processes and are directly involved in infectious diseases. With the ou...

Machine Learning Approach to Facilitate Knowledge Synthesis at the Intersection of Liver Cancer, Epidemiology, and Health Disparities Research.

PURPOSE: Liver cancer is a global challenge, and disparities exist across multiple domains and throughout the disease continuum. However, liver cancer...

Fighting against sudden cardiac death: need for a paradigm shift-Adding near-term prevention and pre-emptive action to long-term prevention.

More than 40 years after the first implantable cardioverter-defibrillator (ICD) implantation, sudden cardiac death (SCD) still accounts for more than ...

Artificial Intelligence in Oncology: Current Capabilities, Future Opportunities, and Ethical Considerations.

The promise of highly personalized oncology care using artificial intelligence (AI) technologies has been forecasted since the emergence of the field....

CapsNet-COVID19: Lung CT image classification method based on CapsNet model.

The outbreak of the Corona Virus Disease 2019 (COVID-19) has posed a serious threat to human health and life around the world. As the number of COVID-...

Translating promise into practice: a review of machine learning in suicide research and prevention.

In ever more pressured health-care systems, technological solutions offering scalability of care and better resource targeting are appealing. Research...

Impact of computational approaches in the fight against COVID-19: an AI guided review of 17 000 studies.

SARS-CoV-2 caused the first severe pandemic of the digital era. Computational approaches have been ubiquitously used in an attempt to timely and effec...

A deep learning method for repurposing antiviral drugs against new viruses via multi-view nonnegative matrix factorization and its application to SARS-CoV-2.

The outbreak of COVID-19 caused by SARS-coronavirus (CoV)-2 has made millions of deaths since 2019. Although a variety of computational methods have b...

A Deep Learning Program to Predict Acute Kidney Injury.

Acute kidney injury is a dangerous and sometime fatal clinical situation, which can cause irreversible damage. If we can predict it earlier and make a...

Contribution of Artificial Intelligence in Pregnancy: A Scoping Review.

For the past ten years, the healthcare sector and industry has witnessed a surge in Artificial Intelligence (AI) technologies being used in many diffe...

Towards gender equity in artificial intelligence and machine learning applications in dermatology.

There has been increased excitement around the use of machine learning (ML) and artificial intelligence (AI) in dermatology for the diagnosis of skin ...

[Next-generation diagnostic pathology].

With the technological progresses and applications of human genome sequencing, bioinformatics analysis and data mining, and molecular pathology and ar...

Electronic surveillance of patient safety events using natural language processing.

OBJECTIVE: We describe our approach to surveillance of reportable safety events captured in hospital data including free-text clinical notes. We hypot...

Health Promotion, Health Literacy and Vaccine Hesitancy: The Role of Humanoid Robots.

The use of humanoid robot technologies within global healthcare settings is rapidly evolving; however, the potential of robots in health promotion and...

Maximum Accuracy Machine Learning Statistical Analysis-A Novel Approach.

Logistic regression is a statistical tool of paramount significance in the field of epidemiology and ranks as one of the most frequently published mul...

Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries.

Suicide attempts are a leading cause of injury globally. Accurate prediction of suicide attempts might offer opportunities for prevention. This case-c...

Clinical Artificial Intelligence Applications in Radiology: Neuro.

Radiologists have been at the forefront of the digitization process in medicine. Artificial intelligence (AI) is a promising area of innovation, parti...