AIMC Topic: Humans

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Application of Convolutional Neural Network for Decoding of 12-Lead Electrocardiogram from a Frequency-Modulated Audio Stream (Sonified ECG).

Sensors (Basel, Switzerland)
Research of novel biosignal modalities with application to remote patient monitoring is a subject of state-of-the-art developments. This study is focused on sonified ECG modality, which can be transmitted as an acoustic wave and received by GSM (Glob...

The Commercial Determinants of Violence: Identifying Opportunities for Violence Prevention through a Public Health-Based Framework Analysis.

International journal of environmental research and public health
Violence has immediate and long-term repercussions for the health of individuals and communities. Recent increases in the understanding of public health approaches to violence prevention have focused on the policies and practices of government, healt...

Generative AI in healthcare: an implementation science informed translational path on application, integration and governance.

Implementation science : IS
BACKGROUND: Artificial intelligence (AI), particularly generative AI, has emerged as a transformative tool in healthcare, with the potential to revolutionize clinical decision-making and improve health outcomes. Generative AI, capable of generating n...

A novel machine-learning framework based on early embryo morphokinetics identifies a feature signature associated with blastocyst development.

Journal of ovarian research
BACKGROUND: Artificial Intelligence entails the application of computer algorithms to the huge and heterogeneous amount of morphodynamic data produced by Time-Lapse Technology. In this context, Machine Learning (ML) methods were developed in order to...

Artificial intelligence in age-related macular degeneration: state of the art and recent updates.

BMC ophthalmology
Age related macular degeneration (AMD) represents a leading cause of vision loss and it is expected to affect 288 million people by 2040. During the last decade, machine learning technologies have shown great potential to revolutionize clinical manag...

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

Scientific reports
Accurately predicting population mortality rates is crucial for effective retirement insurance and economic policy formulation. Recent advancements in deep learning time series forecasting (DLTSF) have led to improved mortality rate predictions compa...

A systematic review of economic evaluation of artificial intelligence-based screening for eye diseases: From possibility to reality.

Survey of ophthalmology
Artificial Intelligence (AI) has become a focus of research in the rapidly evolving field of ophthalmology. Nevertheless, there is a lack of systematic studies on the health economics of AI in this field. We examine studies from the PubMed, Google Sc...

Adaptive activation Functions with Deep Kronecker Neural Network optimized with Bear Smell Search Algorithm for preventing MANET Cyber security attacks.

Network (Bristol, England)
An Adaptive activation Functions with Deep Kronecker Neural Network optimized with Bear Smell Search Algorithm (BSSA) (ADKNN-BSSA-CSMANET) is proposed for preventing MANET Cyber security attacks. The mobile users are enrolled with Trusted Authority U...

A Longitudinal Analysis of Pre- and Post-Operative Dysmorphology in Metopic Craniosynostosis.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
OBJECTIVE: The purpose of this study is to objectively quantify the degree of overcorrection in our current practice and to evaluate longitudinal morphological changes using CranioRate, a novel machine learning skull morphology assessment tool.  Desi...

A Pilot Study Using Machine-learning Algorithms and Wearable Technology for the Early Detection of Postoperative Complications After Cardiothoracic Surgery.

Annals of surgery
OBJECTIVE: To evaluate whether a machine-learning algorithm (ie, the "NightSignal" algorithm) can be used for the detection of postoperative complications before symptom onset after cardiothoracic surgery.