Plastic Surgery

Auto-Segmentation via deep-learning approaches for the assessment of flap volume after reconstructive surgery or radiotherapy in head and neck cancer.

Reconstructive flap surgery aims to restore the substance and function losses associated with tumor resection. Automatic flap segmentation could allow quantification of flap volume and correlations with functional outcomes after surgery or post-operative RT (poRT). Flaps being ectopic tissues of various components (fat, skin, fascia, muscle, bone) of various volume, shape and texture, the anatomic...

Large language models versus traditional textbooks: optimizing learning for plastic surgery case preparation.

BACKGROUND: Large language models (LLMs), such as ChatGPT-4 and Gemini, represent a new frontier in surgical education by offering dynamic, interactive learning experiences. Despite their potential, concerns about the accuracy, depth of knowledge, and bias in LLM responses persist. This study evaluates the effectiveness of LLMs in aiding surgical trainees in plastic and reconstructive surgery thro...

Comparison of Patient Reviews for Submental Liposuction and Kybella Using Deep Learning and Natural Language Processing: Is There a Superior Intervention for Submental Adiposity?

BACKGROUND: Patient-reported outcomes (PROs) are essential in evaluating aesthetic procedures. RealSelf is an online platform for cosmetic and reconst...

Invited Response to "Artificial Intelligence in Rhinoplasty: Precision or Over-Reliance?".

The integration of artificial intelligence (AI) into surgical practice demands critical reflection-not only on its capabilities, but also on its appro...

Surface scanning and imaging in craniofacial surgery.

PURPOSE OF REVIEW: This review describes recent innovations in craniofacial imaging, focusing on emerging techniques such as 3D photogrammetry, smartp...

One Profile to Rule Them All? A Neural Network Analysis of the Homogenizing Effect of Primary Rhinoplasty.

BACKGROUND: A goal of aesthetic rhinoplasty is to improve nasal aesthetics while preserving individuality.

Extremity Soft Tissue Sarcoma Reconstruction Nomograms: A Clinicoradiomic, Machine Learning-Powered Predictor of Postoperative Outcomes.

PURPOSE: The choice of wound closure modality after limb-sparing extremity soft-tissue sarcoma (eSTS) resection is fraught with uncertainty. Leveragin...

AI-Driven Blood Loss Prediction in Large-Volume Liposuction: Enhancing Precision and Patient Safety.

BACKGROUND: Over 2.3 million liposuctions are performed annually with a complication rate of about 5%, including a death rate of 1 in 5,000 due to blo...

Machine learning-based prediction of respiratory depression during sedation for liposuction.

Procedural sedation is often performed by non-anesthesiologists in various settings and can lead to respiratory depression. A tool that enables early ...

Dermocosmetic Bioactive: Safety Assessment and Regulatory Challenges.

OBJECTIVE: This review investigates the regulatory framework for dermocosmetic bioactive in functional skincare, focusing on products with both cosmet...

Artificial Intelligence in Rhinoplasty: Precision or Over-Reliance?

The integration of artificial intelligence (AI) into rhinoplasty has transformed preoperative planning and patient communication by providing highly a...

Whispers beneath the skin: how microneedles are shaping tomorrow's therapies.

Microneedles (MNs) offer a minimally invasive alternative to conventional patch-based and injection-based drug delivery methods. By bypassing first-pa...

Longitudinal changes in minerals are influenced by immunosuppressive treatment in men with granuloma disease.

PURPOSE: To investigate whether granuloma formation following self-administered cosmetic oil injections affects mineral homeostasis, specifically calc...

Quilting Sutures and Suction Drains in Preventing Postoperative Complications in Gynecomastia Surgery.

INTRODUCTION: Gynecomastia is characterized by enlarged breast tissue in men and is often caused by genetic or endocrinological disorders, cancer, or ...

A neural network model for the evolution of reconstructive social learning.

Learning from others is an important adaptation. However, the evolution of social learning and its role in the spread of socially transmitted informat...

Improving Accessibility to Facial Plastic and Reconstructive Surgery Patient Resources Using Artificial Intelligence: A Pilot Study in Patient Education Materials.

The applications of artificial intelligence (AI) are evolving, offering new opportunities to enhance patient care. To determine whether the use of A...

Can artificial ıntelligence detect the anti-aging effect of rhinoplasty?

BACKGROUND: The quest for eternal youth has been a common theme in many cultures for centuries. While we have yet to discover a way to preserve youth ...

Beyond the Mirror: Body Dysmorphic Disorder and Emerging Dysmorphias in Aesthetic Surgery.

Driven by social media and artificial intelligence technologies, new dysmorphias increase pressures on body image, often leading patients to pursue re...

Evidence-based artificial intelligence: Implementing retrieval-augmented generation models to enhance clinical decision support in plastic surgery.

The rapid advancement of large language models (LLMs) has generated significant enthusiasm within healthcare, especially in supporting clinical decisi...

Predicting orthognathic surgery results as postoperative lateral cephalograms using graph neural networks and diffusion models.

Orthognathic surgery, or corrective jaw surgery, is performed to correct severe dentofacial deformities and is increasingly sought for cosmetic purpos...