AIMC Topic: Humans

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LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.

International journal of computer assisted radiology and surgery
PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direc...

Examining the role of artificial intelligence to advance knowledge and address barriers to research in eating disorders.

The International journal of eating disorders
OBJECTIVE: To provide a brief overview of artificial intelligence (AI) application within the field of eating disorders (EDs) and propose focused solutions for research.

Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators.

Cell metabolism
Cellular senescence underlies many aging-related pathologies, but its heterogeneity poses challenges for studying and targeting senescent cells. We present here a machine learning program senescent cell identification (SenCID), which accurately ident...

CRIECNN: Ensemble convolutional neural network and advanced feature extraction methods for the precise forecasting of circRNA-RBP binding sites.

Computers in biology and medicine
Circular RNAs (circRNAs) have surfaced as important non-coding RNA molecules in biology. Understanding interactions between circRNAs and RNA-binding proteins (RBPs) is crucial in circRNA research. Existing prediction models suffer from limited availa...

Leveraging generative AI for clinical evidence synthesis needs to ensure trustworthiness.

Journal of biomedical informatics
Evidence-based medicine promises to improve the quality of healthcare by empowering medical decisions and practices with the best available evidence. The rapid growth of medical evidence, which can be obtained from various sources, poses a challenge ...

The Promise and Challenges of Practice-Oriented Research: A Commentary on the Special Issue.

Administration and policy in mental health
At the centre of POR is the concept of collaboration between patients, therapists, agencies, and third-party payers. For this commentary, I review the articles of the special issue with attention to both the opportunities and challenges offered by pr...

Predicting the wicking rate of nitrocellulose membranes from recipe data: a case study using ANN at a membrane manufacturing in South Korea.

Analytical sciences : the international journal of the Japan Society for Analytical Chemistry
Lateral flow assays have been widely used for detecting coronavirus disease 2019 (COVID-19). A lateral flow assay consists of a Nitrocellulose (NC) membrane, which must have a specific lateral flow rate for the proteins to react. The wicking rate is ...

Food for Thought: Optical Sensor Arrays and Machine Learning for the Food and Beverage Industry.

ACS sensors
Arrays of cross-reactive sensors, combined with statistical or machine learning analysis of their multivariate outputs, have enabled the holistic analysis of complex samples in biomedicine, environmental science, and consumer products. Comparisons ar...

Noninvasive virtual biopsy using micro-registered optical coherence tomography (OCT) in human subjects.

Science advances
Histological hematoxylin and eosin-stained (H&E) tissue sections are used as the gold standard for pathologic detection of cancer, tumor margin detection, and disease diagnosis. Producing H&E sections, however, is invasive and time-consuming. While d...

Dilated Heterogeneous Convolution for Cell Detection and Segmentation Based on Mask R-CNN.

Sensors (Basel, Switzerland)
Owing to the variable shapes, large size difference, uneven grayscale, and dense distribution among biological cells in an image, it is very difficult to accurately detect and segment cells. Especially, it is a serious challenge for some microscope i...