AIMC Topic: Humans

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Development of AI-driven prediction models to realize real-time tumor tracking during radiotherapy.

Radiation oncology (London, England)
BACKGROUND: In infrared reflective (IR) marker-based hybrid real-time tumor tracking (RTTT), the internal target position is predicted with the positions of IR markers attached on the patient's body surface using a prediction model. In this work, we ...

Unsupervised learning of haptic material properties.

eLife
When touching the surface of an object, its spatial structure translates into a vibration on the skin. The perceptual system evolved to translate this pattern into a representation that allows to distinguish between different materials. Here, we show...

Proposing Novel Data Analytics Method for Anatomical Landmark Identification from Endoscopic Video Frames.

Journal of healthcare engineering
BACKGROUND: The anatomical landmarks contain the characteristics that are used to guide the gastroenterologists during the endoscopy. The expert can also ensure the completion of examination with the help of the anatomical landmarks. Automatic detect...

Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction.

Journal of healthcare engineering
This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multiscale sampling frequency of multisource heterogeneous data. The proposed model also demonstrates its su...

Radiological Analysis of COVID-19 Using Computational Intelligence: A Broad Gauge Study.

Journal of healthcare engineering
Pulmonary medical image analysis using image processing and deep learning approaches has made remarkable achievements in the diagnosis, prognosis, and severity check of lung diseases. The epidemic of COVID-19 brought out by the novel coronavirus has ...

New Opportunities, Challenges, and Applications of Edge-AI for Connected Healthcare in Internet of Medical Things for Smart Cities.

Journal of healthcare engineering
Revolution in healthcare can be experienced with the advancement of smart sensorial things, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Internet of Medical Things (IoMT), and edge analytics with the integration of cloud c...

Effective of Smart Mathematical Model by Machine Learning Classifier on Big Data in Healthcare Fast Response.

Computational and mathematical methods in medicine
In the past few years, big data related to healthcare has become more important, due to the abundance of data, the increasing cost of healthcare, and the privacy of healthcare. Create, analyze, and process large and complex data that cannot be proces...

Predicting Chronic Kidney Disease Using Hybrid Machine Learning Based on Apache Spark.

Computational intelligence and neuroscience
Chronic kidney disease (CKD) has become a widespread disease among people. It is related to various serious risks like cardiovascular disease, heightened risk, and end-stage renal disease, which can be feasibly avoidable by early detection and treatm...

Deep Learning-Based Fake Information Detection and Influence Evaluation.

Computational intelligence and neuroscience
With the prevalence of the Internet, a large number of users have participated in OSN (Online Social Networks), which has gradually made it the mainstream way for obtaining news or information from the Internet. However, with the rapid development of...

Application of Unsupervised Migration Method Based on Deep Learning Model in Basketball Training.

Computational intelligence and neuroscience
Nowadays, China's sports industry has attained effective development, but the athlete's efficiency in the training process is too complex to have a scientific guarantee. Machine learning technology's help in guiding the sports training process has be...