AIMC Topic: Humans

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Machine learning based early mortality prediction in the emergency department.

International journal of medical informatics
BACKGROUND: It is a great challenge for emergency physicians to early detect the patient's deterioration and prevent unexpected death through a large amount of clinical data, which requires sufficient experience and keen insight.

Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study.

The Lancet. Digital health
BACKGROUND: Geographic atrophy is a major vision-threatening manifestation of age-related macular degeneration, one of the leading causes of blindness globally. Geographic atrophy has no proven treatment or method for easy detection. Rapid, reliable,...

Dual coding of knowledge in the human brain.

Trends in cognitive sciences
How does the human brain code knowledge about the world? While disciplines such as artificial intelligence represent world knowledge based on human language, neurocognitive models of knowledge have been dominated by sensory embodiment, in which knowl...

Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinic...

Event-Driven Deep Learning for Edge Intelligence (EDL-EI).

Sensors (Basel, Switzerland)
Edge intelligence (EI) has received a lot of interest because it can reduce latency, increase efficiency, and preserve privacy. More significantly, as the Internet of Things (IoT) has proliferated, billions of portable and embedded devices have been ...

Tooth and Bone Parameters in the Assessment of the Chronological Age of Children and Adolescents Using Neural Modelling Methods.

Sensors (Basel, Switzerland)
The analog methods used in the clinical assessment of the patient's chronological age are subjective and characterized by low accuracy. When using those methods, there is a noticeable discrepancy between the chronological age and the age estimated ba...

A Cost-Efficient High-Speed VLSI Architecture for Spiking Convolutional Neural Network Inference Using Time-Step Binary Spike Maps.

Sensors (Basel, Switzerland)
Neuromorphic hardware systems have been gaining ever-increasing focus in many embedded applications as they use a brain-inspired, energy-efficient spiking neural network (SNN) model that closely mimics the human cortex mechanism by communicating and ...

Machine-learning-based COVID-19 mortality prediction model and identification of patients at low and high risk of dying.

Critical care (London, England)
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-Cov2 virus has become the greatest health and controversial issue for worldwide nations. It is associated with different clinical manifestations and a high mortality rate...

Effects of proximal priority and distal priority robotic priming techniques with impairment-oriented training of upper limb functions in patients with chronic stroke: study protocol for a single-blind, randomized controlled trial.

Trials
BACKGROUND: The sequence of establishing a proximal stability or function before facilitation of the distal body part has long been recognized in stroke rehabilitation practice but lacks scientific evidence. This study plans to examine the effects of...