AIMC Topic: Artificial Intelligence

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Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury.

Scientific reports
Traumatic spinal cord injury (SCI) produces a complex syndrome that is expressed across multiple endpoints ranging from molecular and cellular changes to functional behavioral deficits. Effective therapeutic strategies for CNS injury are therefore li...

A pre-training and self-training approach for biomedical named entity recognition.

PloS one
Named entity recognition (NER) is a key component of many scientific literature mining tasks, such as information retrieval, information extraction, and question answering; however, many modern approaches require large amounts of labeled training dat...

Improving burn depth assessment for pediatric scalds by AI based on semantic segmentation of polarized light photography images.

Burns : journal of the International Society for Burn Injuries
This paper illustrates the efficacy of an artificial intelligence (AI) (a convolutional neural network, based on the U-Net), for the burn-depth assessment using semantic segmentation of polarized high-performance light camera images of burn wounds. T...

Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom.

Biological psychiatry. Cognitive neuroscience and neuroimaging
Artificial intelligence (AI) is increasingly employed in health care fields such as oncology, radiology, and dermatology. However, the use of AI in mental health care and neurobiological research has been modest. Given the high morbidity and mortalit...

Recognition of facial expression of fetuses by artificial intelligence (AI).

Journal of perinatal medicine
OBJECTIVES: The development of the artificial intelligence (AI) classifier to recognize fetal facial expressions that are considered as being related to the brain development of fetuses as a retrospective, non-interventional pilot study.

Automatic ganglion cell detection for improving the efficiency and accuracy of hirschprung disease diagnosis.

Scientific reports
Histopathologic diagnosis of Hirschsprung's disease (HSCR) is time consuming and requires expertise. The use of artificial intelligence (AI) in digital pathology is actively researched and may improve the diagnosis of HSCR. The purpose of this resear...

Barrett esophagus: What to expect from Artificial Intelligence?

Best practice & research. Clinical gastroenterology
The evaluation and assessment of Barrett's esophagus is challenging for both expert and nonexpert endoscopists. However, the early diagnosis of cancer in Barrett's esophagus is crucial for its prognosis, and could save costs. Pre-clinical and clinica...

Use of artificial intelligence on Electroencephalogram (EEG) waveforms to predict failure in early school grades in children from a rural cohort in Pakistan.

PloS one
Universal primary education is critical for individual academic growth and overall adult productivity of nations. Estimates indicate that 25% of 59 million primary age out of school children drop out and early grade failure is one of the factors. An ...