AIMC Topic: Artificial Intelligence

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Replacement of animal testing by integrated approaches to testing and assessment (IATA): a call for in vivitrosi.

Archives of toxicology
Alternative methods to animal use in toxicology are evolving with new advanced tools and multilevel approaches, to answer from one side to 3Rs requirements, and on the other side offering relevant and valid tests for drugs and chemicals, considering ...

Challenging molecular dogmas in human sepsis using mathematical reasoning.

EBioMedicine
Sepsis is defined as a dysregulated host-response to infection, across all ages and pathogens. What defines a dysregulated state remains intensively researched but incompletely understood. Here, we dissect the meaning of this definition and its impor...

Identifying the Posture of Young Adults in Walking Videos by Using a Fusion Artificial Intelligent Method.

Biosensors
Many neurological and musculoskeletal disorders are associated with problems related to postural movement. Noninvasive tracking devices are used to record, analyze, measure, and detect the postural control of the body, which may indicate health probl...

Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes.

Alzheimer's research & therapy
IMPORTANCE: The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context.

A deep learning approach identifies new ECG features in congenital long QT syndrome.

BMC medicine
BACKGROUND: Congenital long QT syndrome (LQTS) is a rare heart disease caused by various underlying mutations. Most general cardiologists do not routinely see patients with congenital LQTS and may not always recognize the accompanying ECG features. I...

Deciphering impedance cytometry signals with neural networks.

Lab on a chip
Microfluidic impedance cytometry is a label-free technique for high-throughput single-cell analysis. Multi-frequency impedance measurements provide data that allows full characterisation of cells, linking electrical phenotype to individual biophysica...

Development and Validation of an Explainable Machine Learning Model for Major Complications After Cytoreductive Surgery.

JAMA network open
IMPORTANCE: Cytoreductive surgery (CRS) is one of the most complex operations in surgical oncology with significant morbidity, and improved risk prediction tools are critically needed. Machine learning models can potentially overcome the limitations ...

Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform.

JAMA network open
IMPORTANCE: Predicting postoperative complications has the potential to inform shared decisions regarding the appropriateness of surgical procedures, targeted risk-reduction strategies, and postoperative resource use. Realizing these advantages requi...

Perspectives of Patients About Artificial Intelligence in Health Care.

JAMA network open
This survey study describes the results of a nationally representative survey on artificial intelligence use in health care delivery.