AIMC Topic: Humans

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Prototype early diagnostic model for invasive pulmonary aspergillosis based on deep learning and big data training.

Mycoses
BACKGROUND: Currently, the diagnosis of invasive pulmonary aspergillosis (IPA) mainly depends on the integration of clinical, radiological and microbiological data. Artificial intelligence (AI) has shown great advantages in dealing with data-rich bio...

Identification of Bacterial Pathogens at Genus and Species Levels through Combination of Raman Spectrometry and Deep-Learning Algorithms.

Microbiology spectrum
The rapid and accurate identification of the causing agents during bacterial infections would greatly improve pathogen transmission, prevention, patient care, and medical treatments in clinical settings. Although many conventional and molecular metho...

CATNet: Cross-event attention-based time-aware network for medical event prediction.

Artificial intelligence in medicine
Medical event prediction (MEP) is a fundamental task in the healthcare domain, which needs to predict medical events, including medications, diagnosis codes, laboratory tests, procedures, outcomes, and so on, according to historical medical records o...

Virtual disease landscape using mechanics-informed machine learning: Application to esophageal disorders.

Artificial intelligence in medicine
Esophageal disorders are related to the mechanical properties and function of the esophageal wall. Therefore, to understand the underlying fundamental mechanisms behind various esophageal disorders, it is crucial to map mechanical behavior of the eso...

Graph representation learning in biomedicine and healthcare.

Nature biomedical engineering
Networks-or graphs-are universal descriptors of systems of interacting elements. In biomedicine and healthcare, they can represent, for example, molecular interactions, signalling pathways, disease co-morbidities or healthcare systems. In this Perspe...

Estimation of the Kinematics and Workspace of a Robot Using Artificial Neural Networks.

Sensors (Basel, Switzerland)
At present, in specific and complex industrial operations, robots have to respect certain requirements and criteria as high kinematic or dynamic performance, specific dimensions of the workspace, or limitation of the dimensions of the mobile elements...

Teaching, Learning and Assessing Anatomy with Artificial Intelligence: The Road to a Better Future.

International journal of environmental research and public health
Anatomy is taught in the early years of an undergraduate medical curriculum. The subject is volatile and of voluminous content, given the complex nature of the human body. Students frequently face learning constraints in these fledgling years of medi...

Value assessment of artificial intelligence in medical imaging: a scoping review.

BMC medical imaging
BACKGROUND: Artificial intelligence (AI) is seen as one of the major disrupting forces in the future healthcare system. However, the assessment of the value of these new technologies is still unclear, and no agreed international health technology ass...

Positive surgical margin's impact on short-term oncological prognosis after robot-assisted partial nephrectomy (MARGINS study: UroCCR no 96).

Scientific reports
The oncological impact of positive surgical margins (PSM) after robot-assisted partial nephrectomy (RAPN) is still under debate. We compared PSM and Negative Surgical Margins (NSM) in terms of recurrence-free survival (RFS), metastasis-free survival ...

Automated detection of patterned single-cells within hydrogel using deep learning.

Scientific reports
Single-cell analysis has been widely used in various biomedical engineering applications, ranging from cancer diagnostics, and immune response monitoring to drug screening. Single-cell isolation is fundamental for observing single-cell activities and...