AIMC Topic: Humans

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Integrating artificial intelligence, machine learning, and deep learning approaches into remediation of contaminated sites: A review.

Chemosphere
The growing number of contaminated sites across the world pose a considerable threat to the environment and human health. Remediating such sites is a cumbersome process with the complexity originating from the need for extensive sampling and testing ...

An unsupervised learning approach to identify immunoglobulin utilization patterns using electronic health records.

Transfusion
BACKGROUND: Managing Canada's immunoglobulin (Ig) product resource allocation is challenging due to increasing demand, high expenditure, and global shortages. Detection of groups with high utilization rates can help with resource planning for Ig prod...

[Legal integration of artificial intelligence into internal medicine : Data protection, regulatory, reimbursement and liability questions].

Innere Medizin (Heidelberg, Germany)
Artificial intelligence (AI) opens up new opportunities to improve medical care in internal medicine; however, legal uncertainties in the application of AI impede its integration into the daily practice of internal medicine. To clarify the situation ...

[Faster diagnosis of rare diseases with artificial intelligence-A precept of ethics, economy and quality of life].

Innere Medizin (Heidelberg, Germany)
BACKGROUND: Approximately 300 million people worldwide suffer from a rare disease. An optimal treatment requires a successful diagnosis. This takes a particularly long time, especially for rare diseases. Digital diagnosis support systems could be imp...

Amharic political sentiment analysis using deep learning approaches.

Scientific reports
This study delves into the realm of sentiment analysis in the Amharic language, focusing on political sentences extracted from social media platforms in Ethiopia. The research employs deep learning techniques, including Convolutional Neural Networks ...

Stingy bots can improve human welfare in experimental sharing networks.

Scientific reports
Machines powered by artificial intelligence increasingly permeate social networks with control over resources. However, machine allocation behavior might offer little benefit to human welfare over networks when it ignores the specific network mechani...

Transfer learning for accurate fetal organ classification from ultrasound images: a potential tool for maternal healthcare providers.

Scientific reports
Ultrasound imaging is commonly used to aid in fetal development. It has the advantage of being real-time, low-cost, non-invasive, and easy to use. However, fetal organ detection is a challenging task for obstetricians, it depends on several factors, ...

A novel bidirectional LSTM deep learning approach for COVID-19 forecasting.

Scientific reports
COVID-19 has resulted in significant morbidity and mortality globally. We develop a model that uses data from thirty days before a fixed time point to forecast the daily number of new COVID-19 cases fourteen days later in the early stages of the pand...

SONAR, a nursing activity dataset with inertial sensors.

Scientific data
Accurate and comprehensive nursing documentation is essential to ensure quality patient care. To streamline this process, we present SONAR, a publicly available dataset of nursing activities recorded using inertial sensors in a nursing home. The data...

Use of Artificial Intelligence in the Identification and Diagnosis of Frailty Syndrome in Older Adults: Scoping Review.

Journal of medical Internet research
BACKGROUND: Frailty syndrome (FS) is one of the most common noncommunicable diseases, which is associated with lower physical and mental capacities in older adults. FS diagnosis is mostly focused on biological variables; however, it is likely that th...