AIMC Topic: Humans

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Stratifying High-Risk Thyroid Nodules Using a Novel Deep Learning System.

Experimental and clinical endocrinology & diabetes : official journal, German Society of Endocrinology [and] German Diabetes Association
INTRODUCTION: The current ultrasound scan classification system for thyroid nodules is time-consuming, labor-intensive, and subjective. Artificial intelligence (AI) has been shown to increase the accuracy of predicting the malignancy rate of thyroid ...

Medical applications of generative adversarial network: a visualization analysis.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Deep learning (DL) is one of the latest approaches to artificial intelligence. As an unsupervised DL method, a generative adversarial network (GAN) can be used to synthesize new data.

Multiple switching between the biosimilar adalimumab PF-06410293 and reference adalimumab in patients with active rheumatoid arthritis: a phase 3, open-label, randomised, parallel-group study.

The Lancet. Rheumatology
BACKGROUND: An adalimumab biosimilar with an interchangeability designation could increase access to effective treatment for more patients. We aimed to assess the interchangeability of adalimumab biosimilar PF-06410293 (adalimumab-afzb) and reference...

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Proceedings of the National Academy of Sciences of the United States of America
Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal rema...

Enhanced Deep Learning Approach for Accurate Eczema and Psoriasis Skin Detection.

Sensors (Basel, Switzerland)
This study presents an enhanced deep learning approach for the accurate detection of eczema and psoriasis skin conditions. Eczema and psoriasis are significant public health concerns that profoundly impact individuals' quality of life. Early detectio...

Feature-aware unsupervised lesion segmentation for brain tumor images using fast data density functional transform.

Scientific reports
We demonstrate that isomorphically mapping gray-level medical image matrices onto energy spaces underlying the framework of fast data density functional transform (fDDFT) can achieve the unsupervised recognition of lesion morphology. By introducing t...

Deep learning-based postoperative visual acuity prediction in idiopathic epiretinal membrane.

BMC ophthalmology
BACKGROUND: To develop a deep learning (DL) model based on preoperative optical coherence tomography (OCT) training to automatically predict the 6-month postoperative visual outcomes in patients with idiopathic epiretinal membrane (iERM).

A subcomponent-guided deep learning method for interpretable cancer drug response prediction.

PLoS computational biology
Accurate prediction of cancer drug response (CDR) is a longstanding challenge in modern oncology that underpins personalized treatment. Current computational methods implement CDR prediction by modeling responses between entire drugs and cell lines, ...

De novo drug design based on patient gene expression profiles via deep learning.

Molecular informatics
Computational de novo drug design is a challenging issue in medicine, and it is desirable to consider all of the relevant information of the biological systems in a disease state. Here, we propose a novel computational method to generate drug candida...

Humans and robots: Friends of the future? A bird's eye view of biomanufacturing industry 5.0.

Biotechnology advances
The evolution of industries have introduced versatile technologies, motivating limitless possibilities of tackling pivotal global predicaments in the arenas of medicine, environment, defence, and national security. In this direction, ardently emerges...