AIMC Topic: Humans

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Memristor-based analogue computing for brain-inspired sound localization with in situ training.

Nature communications
The human nervous system senses the physical world in an analogue but efficient way. As a crucial ability of the human brain, sound localization is a representative analogue computing task and often employed in virtual auditory systems. Different fro...

Evaluation of fully automated cephalometric measurements obtained from web-based artificial intelligence driven platform.

BMC oral health
BACKGROUND: Artificial Intelligence has created a huge impact in different areas of dentistry. Automated cephalometric analysis is one of the major applications of artificial intelligence in the field of orthodontics. Various automated cephalometric ...

Does conventional morphological evaluation still play a role in predicting blastocyst formation?

Reproductive biology and endocrinology : RB&E
BACKGROUND: Advanced models including time-lapse imaging and artificial intelligence technologies have been used to predict blastocyst formation. However, the conventional morphological evaluation of embryos is still widely used. The purpose of the p...

Application of unsupervised deep learning algorithms for identification of specific clusters of chronic cough patients from EMR data.

BMC bioinformatics
BACKGROUND: Chronic cough affects approximately 10% of adults. The lack of ICD codes for chronic cough makes it challenging to apply supervised learning methods to predict the characteristics of chronic cough patients, thereby requiring the identific...

Microscopic nuclei classification, segmentation, and detection with improved deep convolutional neural networks (DCNN).

Diagnostic pathology
BACKGROUND: Nuclei classification, segmentation, and detection from pathological images are challenging tasks due to cellular heterogeneity in the Whole Slide Images (WSI).

The stability of oncologic MRI radiomic features and the potential role of deep learning: a review.

Physics in medicine and biology
The use of MRI radiomic models for the diagnosis, prognosis and treatment response prediction of tumors has been increasingly reported in literature. However, its widespread adoption in clinics is hampered by issues related to features stability. In ...

The future of early cancer detection.

Nature medicine
A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish in...

Online Course Model of Social and Political Education Using Deep Learning.

Computational intelligence and neuroscience
This study aims to improve the social and political literacy of college students. Social and Political Education (SPE) is studied for undergraduates. Firstly, the background of the subject research is introduced. The face recognition module is built ...

Deep Learning-Based Ultrasound Combined with Gastroscope for the Diagnosis and Nursing of Upper Gastrointestinal Submucous Lesions.

Computational and mathematical methods in medicine
The study focused on the diagnostic value of deep learning-based ultrasound combined with gastroscope examination for upper gastrointestinal submucous lesions and nursing. A total of 104 patients with upper gastrointestinal submucous lesions diagnose...

Predicting diarrhoea outbreaks with climate change.

PloS one
BACKGROUND: Climate change is expected to exacerbate diarrhoea outbreaks across the developing world, most notably in Sub-Saharan countries such as South Africa. In South Africa, diseases related to diarrhoea outbreak is a leading cause of morbidity ...