AIMC Topic: Humans

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Deep neural networks can differentiate thyroid pathologies on infrared hyperspectral images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The thyroid is a gland responsible for producing important body hormones. Several pathologies can affect this gland, such as thyroiditis, hypothyroidism, and thyroid cancer. The visual histological analysis of thyroid specim...

Classification of posttransfusion adverse events using a publicly available artificial intelligence system.

Transfusion
BACKGROUND: Correct classification of transfusion reactions is important not only for effective patient care and donor management but also for accurate tracking of events in hemovigilance systems. We compared the ability of a generative artificial in...

dbCRAF: a curated knowledgebase for regulation of radiation response in human cancer.

NAR cancer
Radiation therapy (RT) is one of the primary treatment modalities of cancer, with 40-60% of cancer patients benefiting from RT during their treatment course. The intrinsic radiosensitivity or acquired radioresistance of tumor cells would affect the r...

Improving Computer-Aided Thoracic Disease Diagnosis through Comparative Analysis Using Chest X-ray Images Taken at Different Times.

Sensors (Basel, Switzerland)
Medical professionals in thoracic medicine routinely analyze chest X-ray images, often comparing pairs of images taken at different times to detect lesions or anomalies in patients. This research aims to design a computer-aided diagnosis system that ...

Synthetic Corpus Generation for Deep Learning-Based Translation of Spanish Sign Language.

Sensors (Basel, Switzerland)
Sign language serves as the primary mode of communication for the deaf community. With technological advancements, it is crucial to develop systems capable of enhancing communication between deaf and hearing individuals. This paper reviews recent sta...

A cognitive deep learning approach for medical image processing.

Scientific reports
In ophthalmic diagnostics, achieving precise segmentation of retinal blood vessels is a critical yet challenging task, primarily due to the complex nature of retinal images. The intricacies of these images often hinder the accuracy and efficiency of ...

Novel antimicrobial peptides against Cutibacterium acnes designed by deep learning.

Scientific reports
The increasing prevalence of antibiotic resistance in Cutibacterium acnes (C. acnes) requires the search for alternative therapeutic strategies. Antimicrobial peptides (AMPs) offer a promising avenue for the development of new treatments targeting C....

Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model.

Scientific reports
Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and results in severe depression and suicide attempts in the social community. Prompt actions are crucial in tackling PPDD, which requires a quick recognition and accurate a...

Rapid deep learning-assisted predictive diagnostics for point-of-care testing.

Nature communications
Prominent techniques such as real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and rapid kits are currently being explored to both enhance sensitivity and reduce assay time for diagnostic tests. Existing commerc...

Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review.

BMC oral health
BACKGROUND: The aim of this systematic review is to evaluate the diagnostic performance of Artificial Intelligence (AI) models designed for the detection of caries lesion (CL).