AIMC Topic: Humans

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The Study of Immersive Physiology Courses Based on Intelligent Network through Virtual Reality Technology in the Context of 5G.

Computational intelligence and neuroscience
The current boom in Internet technology has paved the way for the research and evolution of various technologies related to it. One such technology is immersive virtual reality (IVR). Immersive technology is referred to as creating a reality-like exp...

Analysis of English Cultural Teaching Model Based on Machine Learning.

Computational intelligence and neuroscience
According to the world population, nearly five billion people use mobile phones in their daily lives, and this has increased by 20% in the last twelve months compared to the previous report. An average survey conducted by researchers to find the amou...

Study on Integration and Application of Artificial Intelligence and Wireless Network in Piano Music Teaching.

Computational intelligence and neuroscience
Until 2019, most people had never faced the situation that would be their life-changing moment. Most universities are conducting classes for their students with the help of virtual classrooms indicating massive technological growth. However, this dev...

Deep learning-based insights on T:R ratio behaviour during prolonged screening for S-ICD eligibility.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing
BACKGROUND: A major predictor of eligibility of subcutaneous implantable cardiac defibrillators (S-ICD) is the T:R ratio. The eligibility cut-off of the T:R ratio incorporates a safety margin to accommodate for fluctuations of ECG signal amplitudes. ...

Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care.

Academic pediatrics
BACKGROUND: Family engagement is critical in the implementation of artificial intelligence (AI)-based clinical decision support tools, which will play an increasing role in health care in the future. We sought to understand parental perceptions of co...

Deep Learning Applications in Surgery: Current Uses and Future Directions.

The American surgeon
Deep learning (DL) is a subset of machine learning that is rapidly gaining traction in surgical fields. Its tremendous capacity for powerful data-driven problem-solving has generated computational breakthroughs in many realms, with the fields of medi...

Artificial Intelligence and Machine Learning in Prediction of Surgical Complications: Current State, Applications, and Implications.

The American surgeon
Surgical complications pose significant challenges for surgeons, patients, and health care systems as they may result in patient distress, suboptimal outcomes, and higher health care costs. Artificial intelligence (AI)-driven models have revolutioniz...

Special issue "The advance of solid tumor research in China": Prognosis prediction for stage II colorectal cancer by fusing computed tomography radiomics and deep-learning features of primary lesions and peripheral lymph nodes.

International journal of cancer
Currently, the prognosis assessment of stage II colorectal cancer (CRC) remains a difficult clinical problem; therefore, more accurate prognostic predictors must be developed. In our study, we developed a prognostic prediction model for stage II CRC ...

Robot-assisted thoracic surgery for lung cancer patients with incomplete fissure.

Surgical endoscopy
BACKGROUND: Robot-assisted thoracic surgery has gradually been accepted as an alternative treatment for early-stage non-small-cell lung cancer (NSCLC) owing to its advantages. However, severe incomplete interlobar fissure may lead to a high rate of c...

Deep Reinforcement Learning with Automated Label Extraction from Clinical Reports Accurately Classifies 3D MRI Brain Volumes.

Journal of digital imaging
Image classification is probably the most fundamental task in radiology artificial intelligence. To reduce the burden of acquiring and labeling data sets, we employed a two-pronged strategy. We automatically extracted labels from radiology reports in...