AI Article Synopsis

Article Abstract

Within the field of cosmetic dermatology, several promising developments utilize artificial intelligence to better patient care. While many new treatments in cosmetic dermatology feature components of artificial intelligence, there is a knowledge gap within the field regarding the current and developing products featuring AI. We aim to highlight current and developing applications of artificial intelligence in cosmetic dermatology and provide insight into future modalities in this field. Methods include literature review, including peer-reviewed journal articles as well as product websites. In an age of medical and technological advancement, the utility of artificial intelligence models continues to grow.There are many new facets of artificial intelligence in cosmetic dermatology, marketed to both the consumer and the physician. With the development of customizable skin care, augmented reality applications, and at-home skin analysis tools, patients are empowered to be the masters of their cosmetic care. Artificial intelligence is utilized by physicians in new ways in their practices, with the advent of models for prediction of clinical outcome to treatments and tools for in-depth analysis of the patient's skin. Further research is required in the development of automated energy-based treatment devices and robotic-assisted treatments. Models for AI in cosmetic dermatology serve to increase patient involvement in their skin care decisions and have the ability to enhance the patient-physician experience. Dermatologists should be well-informed of the emerging technologies to better educate patients and enhance their clinical practice.

Download full-text PDF

Source
http://dx.doi.org/10.1111/jocd.13797DOI Listing

Publication Analysis

Top Keywords

artificial intelligence
28
cosmetic dermatology
20
intelligence cosmetic
12
current developing
8
skin care
8
intelligence
7
cosmetic
7
artificial
6
dermatology
5
role artificial
4

Similar Publications

Role of immune cell homeostasis in research and treatment response in hepatocellular carcinoma.

Clin Exp Med

January 2025

Department of Thoracic Surgery, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, China.

Introduction Recently, immune cells within the tumor microenvironment (TME) have become crucial in regulating cancer progression and treatment responses. The dynamic interactions between tumors and immune cells are emerging as a promising strategy to activate the host's immune system against various cancers. The development and progression of hepatocellular carcinoma (HCC) involve complex biological processes, with the role of the TME and tumor phenotypes still not fully understood.

View Article and Find Full Text PDF

The brain undergoes atrophy and cognitive decline with advancing age. The utilization of brain age prediction represents a pioneering methodology in the examination of brain aging. This study aims to develop a deep learning model with high predictive accuracy and interpretability for brain age prediction tasks.

View Article and Find Full Text PDF

This review aimed to explore the impact of extrusion on Andean grains, such as quinoa, kañiwa, and kiwicha, highlighting their macromolecular transformations, technological innovations, and contributions to food security. These grains, which are rich in starch, high-quality proteins, and antioxidant compounds, are versatile raw materials for extrusion, a continuous and efficient process that combines high temperatures and pressures to transform structural and chemical components. Extrusion improves the digestibility of proteins and starches, encourages the formation of amylose-lipid complexes, and increases the solubility of dietary fiber.

View Article and Find Full Text PDF

Metabolomics provide a promising tool for understanding dementia pathogenesis and identifying novel biomarkers. This study aimed to identify amino acid biomarkers for Alzheimer's Disease (AD) and Vascular Dementia (VD). By amino acid metabolomics, the concentrations of amino acids were determined in the serum of AD and VD patients as well as age-matched healthy controls.

View Article and Find Full Text PDF

Development and Validation of KCPREDICT: A Deep Learning Model for Early Detection of Coronary Artery Lesions in Kawasaki Disease Patients.

Pediatr Cardiol

January 2025

Department of Infectious Disease, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, No. 1678 Dongfang Road, Pudong New Area, Shanghai, 200127, China.

Kawasaki disease (KD) is a febrile vasculitis disorder, with coronary artery lesions (CALs) being the most severe complication. Early detection of CALs is challenging due to limitations in echocardiographic equipment (UCG). This study aimed to develop and validate an artificial intelligence algorithm to distinguish CALs in KD patients and support diagnostic decision-making at admission.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!