AIMC Topic: Humans

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Protein loop structure prediction by community-based deep learning and its application to antibody CDR H3 loop modeling.

PLoS computational biology
As of now, more than 60 years have passed since the first determination of protein structures through crystallography, and a significant portion of protein structures can be predicted by computers. This is due to the groundbreaking enhancement in pro...

Integrated analysis of single-cell sequencing and machine learning identifies a signature based on monocyte/macrophage hub genes to analyze the intracranial aneurysm associated immune microenvironment.

Frontiers in immunology
Monocytes are pivotal immune cells in eliciting specific immune responses and can exert a significant impact on the progression, prognosis, and immunotherapy of intracranial aneurysms (IAs). The objective of this study was to identify monocyte/macrop...

Group-informed attentive framework for enhanced diabetes mellitus progression prediction.

Frontiers in endocrinology
The increasing prevalence of Diabetes Mellitus (DM) as a global health concern highlights the paramount importance of accurately predicting its progression. This necessity has propelled the use of deep learning's advanced analytical and predictive ca...

The potential role and restrictions of artificial intelligence in medical school dermatology education.

Clinics in dermatology
Artificial intelligence (AI) is a rapidly developing field with the potential to transform various aspects of health care and public health, including medical training. The use of AI is still being studied to understand better how to integrate its in...

Artificial intelligence for nonmelanoma skin cancer.

Clinics in dermatology
Nonmelanoma skin cancers (NMSCs) are among the top five most common cancers globally. NMSC is an area with great potential for novel application of diagnostic tools including artificial intelligence (AI). In this scoping review, we aimed to describe ...

The role of artificial intelligence in cardiovascular magnetic resonance imaging.

Progress in cardiovascular diseases
Cardiovascular magnetic resonance (CMR) imaging is the gold standard test for myocardial tissue characterization and chamber volumetric and functional evaluation. However, manual CMR analysis can be time-consuming and is subject to intra- and inter-o...

Determination of prognostic markers for COVID-19 disease severity using routine blood tests and machine learning.

Anais da Academia Brasileira de Ciencias
The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This ...

A novel approach for APT attack detection based on feature intelligent extraction and representation learning.

PloS one
Advanced Persistent Threat (APT) attacks are causing a lot of damage to critical organizations and institutions. Therefore, early detection and warning of APT attack campaigns are very necessary today. In this paper, we propose a new approach for APT...

Enhancing semantic segmentation in chest X-ray images through image preprocessing: ps-KDE for pixel-wise substitution by kernel density estimation.

PloS one
BACKGROUND: In medical imaging, the integration of deep-learning-based semantic segmentation algorithms with preprocessing techniques can reduce the need for human annotation and advance disease classification. Among established preprocessing techniq...

Video-Based Detection of Freezing of Gait in Daily Clinical Practice in Patients With Parkinsonism.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Freezing of gait (FoG) is a prevalent symptom among individuals with Parkinson's disease and related disorders. FoG detection from videos has been developed recently; however, the process requires using videos filmed within a controlled environment. ...