AIMC Topic: Artificial Intelligence

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An objective skin-type classification based on non-invasive biophysical parameters.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Despite the invention of various non-invasive bioengineering tools, skin-type analysis has largely been based on subjective assessments. However, advancements in the functional cosmetic industry and artificial intelligence-assisted dermat...

Comparison of machine learning and deep learning for view identification from cardiac magnetic resonance images.

Clinical imaging
BACKGROUND: Artificial intelligence is increasingly utilized to aid in the interpretation of cardiac magnetic resonance (CMR) studies. One of the first steps is the identification of the imaging plane depicted, which can be achieved by both deep lear...

Breast imaging: Beyond the detection.

European journal of radiology
Breast cancer is a heterogeneous disease nowadays, including different biological subtypes with a variety of possible treatments, which aim to achieve the best outcome in terms of response to therapy and overall survival. In recent years breast imagi...

Research on Practical Intelligent Mode of Digital Image Economy Based on Improved Genetic Multilayer Neural Network.

Computational intelligence and neuroscience
In the context of economic globalization and digitization, the current financial field is in an unprecedented complex situation. The methods and means to deal with this complexity are developing towards image intelligence. This paper takes financial ...

Using an artificial intelligence tool can be as accurate as human assessors in level one screening for a systematic review.

Health information and libraries journal
BACKGROUND: Artificial intelligence (AI) offers a promising solution to expedite various phases of the systematic review process such as screening.

The prediction of surgical complications using artificial intelligence in patients undergoing major abdominal surgery: A systematic review.

Surgery
BACKGROUND: Conventional statistics are based on a simple cause-and-effect principle. Postoperative complications, however, have a multifactorial and interrelated etiology. The application of artificial intelligence might be more accurate to predict ...

ASO Author Reflections: Applications of Artificial Intelligence in Oesophago-Gastric Malignancies-Present Work and Future Directions.

Annals of surgical oncology
Our paper highlights the use of artificial intelligence (AI) in oesophageal and gastric malignancies with acceptable levels of accuracy for both diagnostic and surveillance purposes. Here, we comment on the past, present and future work necessary for...

NeuroLISP: High-level symbolic programming with attractor neural networks.

Neural networks : the official journal of the International Neural Network Society
Despite significant improvements in contemporary machine learning, symbolic methods currently outperform artificial neural networks on tasks that involve compositional reasoning, such as goal-directed planning and logical inference. This illustrates ...

Evolution of single-lead ECG for STEMI detection using a deep learning approach.

International journal of cardiology
BACKGROUND: While ST-Elevation Myocardial Infarction (STEMI) door-to-balloon times are often below 90 min, symptom to door times remain long at 2.5-h, due at least in part to a delay in diagnosis.