Health Policy

Detection of biomagnetic signals from induced pluripotent stem cell-derived cardiomyocytes using deep learning with simulation data.

The detection of spontaneous magnetic signals can be used for the non-invasive electrophysiological evaluation of induced pluripotent stem cell-derived cardiomyocytes (iPS-CMs). We report that deep learning with a dataset that combines magnetic signals estimated using numerical simulation and actual noise data is effective in the detection of weak biomagnetic signals. To verify the feasibility of ...

Cost-Effectiveness of Artificial Intelligence-Based Opportunistic Compression Fracture Screening of Existing Radiographs.

PURPOSE: Osteoporotic vertebral compression fractures (OVCFs) are a highly prevalent source of morbidity and mortality, and preventive treatment has been demonstrated to be both effective and cost effective. To take advantage of the information available on existing chest and abdominal radiographs, the authors' study group has developed software to access these radiographs for OVCFs with high sens...

Pathways to democratized healthcare: Envisioning human-centered AI-as-a-service for customized diagnosis and rehabilitation.

The ongoing digital revolution in the healthcare sector, emphasized by bodies like the US Food and Drug Administration (FDA), is paving the way for a ...

Industrially Scalable Textile Sensing Interfaces for Extended Artificial Tactile and Human Motion Monitoring without Compromising Comfort.

Smart wearables with the capability for continuous monitoring, perceiving, and understanding human tactile and motion signals, while ensuring comfort,...

Diagnosing glaucoma in primary eye care and the role of Artificial Intelligence applications for reducing the prevalence of undetected glaucoma in Australia.

Glaucoma is the commonest cause of irreversible blindness worldwide, with over 70% of people affected remaining undiagnosed. Early detection is crucia...

Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes.

OBJECTIVE: This study aims to explore the opinions on the insurance coverage of artificial intelligence (AI), as categorized based on the distinct val...

Advancing mortality rate prediction in European population clusters: integrating deep learning and multiscale analysis.

Accurately predicting population mortality rates is crucial for effective retirement insurance and economic policy formulation. Recent advancements in...

Digital technologies to unlock safe and sustainable opportunities for medical device and healthcare sectors with a focus on the combined use of digital twin and extended reality applications: A review.

Medical devices have increased in complexity where there is a pressing need to consider design thinking and specialist training for manufacturers, hea...

The infant health effects of doulas: Leveraging big data and machine learning to inform cost-effective targeting.

Doula services represent an underutilized maternal and child health intervention with the potential to improve outcomes through the provision of physi...

[Analysis of the challenges and dilemmas that bioethics of the 21st century will face in the digital health era].

The medical history underscores the significance of ethics in each advancement, with bioethics playing a pivotal role in addressing emerging ethical c...

Healthcare Systems and Artificial Intelligence: Focus on Challenges and the International Regulatory Framework.

BACKGROUND: Nowadays, healthcare systems are coping with the challenge of countering the exponential growth of healthcare costs worldwide, to support ...

Spatiotemporal assessment of groundwater quality and quantity using geostatistical and ensemble artificial intelligence tools.

The study investigated the spatiotemporal relationship between surface hydrological variables and groundwater quality/quantity using geostatistical an...

Denial-Artificial Intelligence Tools and Health Insurance Coverage Decisions.

Surviving ChatGPT in healthcare.

At the dawn of of Artificial General Intelligence (AGI), the emergence of large language models such as ChatGPT show promise in revolutionizing health...

Effect of insurance status on perioperative outcomes after robotic pancreaticoduodenectomy: a propensity-score matched analysis.

The influence of Medicaid or being uninsured is prevailingly thought to negatively impact a patient's socioeconomic and postoperative course, yet litt...

Improving Access to Eye Care Through Community Health Screenings Using Artificial Intelligence.

PURPOSE: To the best of our knowledge, implementation of artificial intelligence (AI)-based vision screening in community health fair settings has not...

Machine Learning and Bias in Medical Imaging: Opportunities and Challenges.

Bias in health care has been well documented and results in disparate and worsened outcomes for at-risk groups. Medical imaging plays a critical role ...

Conversational artificial intelligence: the interface with the patient concerns inventory.

The patient concerns inventory (PCI) allows patients to highlight the issues they would like to discuss at their outpatient consultation. It improves ...

Telehealth-Enabled In-Home Elbow Rehabilitation for Brachial Plexus Injuries Using Deep-Reinforcement-Learning-Assisted Telepresence Robots.

Due to damage to the network of nerves that regulate the muscles and feeling in the shoulder, arm, and forearm, brachial plexus injuries (BPIs) are kn...

Automatic de-identification of French electronic health records: a cost-effective approach exploiting distant supervision and deep learning models.

BACKGROUND: Electronic health records (EHRs) contain valuable information for clinical research; however, the sensitive nature of healthcare data pres...