AIMC Topic: Humans

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Morphological features of single cells enable accurate automated classification of cancer from non-cancer cell lines.

Scientific reports
Accurate cancer detection and diagnosis is of utmost importance for reliable drug-response prediction. Successful cancer characterization relies on both genetic analysis and histological scans from tumor biopsies. It is known that the cytoskeleton is...

Weakly-supervised deep learning for ultrasound diagnosis of breast cancer.

Scientific reports
Conventional deep learning (DL) algorithm requires full supervision of annotating the region of interest (ROI) that is laborious and often biased. We aimed to develop a weakly-supervised DL algorithm that diagnosis breast cancer at ultrasound without...

Integrative measurement analysis via machine learning descriptor selection for investigating physical properties of biopolymers in hairs.

Scientific reports
Integrative measurement analysis of complex subjects, such as polymers is a major challenge to obtain comprehensive understanding of the properties. In this study, we describe analytical strategies to extract and selectively associate compositional i...

Multi-step ahead predictive model for blood glucose concentrations of type-1 diabetic patients.

Scientific reports
Continuous monitoring of blood glucose (BG) levels is a key aspect of diabetes management. Patients with Type-1 diabetes (T1D) require an effective tool to monitor these levels in order to make appropriate decisions regarding insulin administration a...

Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy.

Scientific reports
Persistent infection with high-risk types Human Papillomavirus could cause diseases including cervical cancers and oropharyngeal cancers. Nonetheless, so far there is no effective pharmacotherapy for treating the infection from high-risk HPV types, a...

Assessing red blood cell deformability from microscopy images using deep learning.

Lab on a chip
Red blood cells (RBCs) must be highly deformable to transit through the microvasculature to deliver oxygen to tissues. The loss of RBC deformability resulting from pathology, natural aging, or storage in blood bags can impede the proper function of t...

SWIFT: A deep learning approach to prediction of hypoxemic events in critically-Ill patients using SpO2 waveform prediction.

PLoS computational biology
Hypoxemia is a significant driver of mortality and poor clinical outcomes in conditions such as brain injury and cardiac arrest in critically ill patients, including COVID-19 patients. Given the host of negative clinical outcomes attributed to hypoxe...

Finite Element Assessment of Bone Fragility from Clinical Images.

Current osteoporosis reports
PURPOSE OF REVIEW: We re-evaluated clinical applications of image-to-FE models to understand if clinical advantages are already evident, which proposals are promising, and which questions are still open.

Machine Learning of Medical Applications Involving Complicated Proteins and Genetic Measurements.

Computational intelligence and neuroscience
. Breast cancer is the second greatest cause of cancer mortality among women, according to the World Health Organization (WHO), and one of the most frequent illnesses among all women today. The influence is not confined to industrialized nations but ...

Artificial Neural Network Analysis-Based Immune-Related Signatures of Primary Non-Response to Infliximab in Patients With Ulcerative Colitis.

Frontiers in immunology
Infliximab (IFX) is an effective medication for ulcerative colitis (UC) patients. However, one-third of UC patients show primary non-response (PNR) to IFX. Our study analyzed three Gene Expression Omnibus (GEO) datasets and used the RobustRankAggreg ...