Publications by authors named "Darlene King"

Purpose Of Review: This paper provides an overview of generative artificial intelligence (AI) and the possible implications in the delivery of mental health care.

Recent Findings: Generative AI is a powerful technology that is changing rapidly. As psychiatrists, it is important for us to understand generative AI technology and how it may impact our patients and our practice of medicine.

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There are over 10,000 mental health and wellness apps on the market. Apps offer the opportunity to increase access to mental health care. However, with many apps to choose from and an app landscape that is largely unregulated, it can be difficult to incorporate this technology into clinical practice.

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The app evaluation framework of the American Psychiatric Association (APA) has emerged as an adaptable tool for those seeking to navigate the ever-growing space of mental health apps. The authors describe a meeting convened in December 2019 to refine the APA framework. The expert panel comprised 16 individuals across health care fields, with representation from psychiatry, psychology, social work, nursing, clinical informatics, peer support specialists, and individuals with lived mental health experience.

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Major depressive disorder is associated with pro-inflammatory markers, such as cytokines TNF-alpha, IL-6, IL-1ß, and C-reactive protein. Galectin-3 is a novel emerging biomarker with pro-inflammatory properties. It is a saccharide binding protein distributed throughout many tissues with varying functions and is a predictor of poor outcomes in patients with heart failure and stroke.

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Galectin-3 (Gal3) is expressed by microglia and performs functions including adhesion; activation of macrophages and fibroblasts, and mediates inflammatory responses in the hippocampus. The present study examined whether serum Gal3 levels predict hippocampal volume in a multi-ethnic, community-based sample. Results of a multiple linear regression (controlling for depression, serum creatinine level, age, BMI, total brain volume, MoCA score, sex, ethnicity, smoking status, history of diabetes) showed that Gal3 levels significantly predicted left (p = .

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The process of burn debridement is a challenging technique requiring significant skills to identify the regions that need excision and their appropriate excision depths. In order to assist surgeons, a machine learning tool is being developed to provide a quantitative assessment of burn-injured tissue. This paper presents three non-invasive optical imaging techniques capable of distinguishing four kinds of tissue-healthy skin, viable wound bed, shallow burn, and deep burn-during serial burn debridement in a porcine model.

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Noncontact photoplethysmography (PPG) has been studied as a method to provide low-cost, noninvasive, two-dimensional blood oxygenation measurements and medical imaging for a variety of near-surface pathologies. To evaluate this technology in a laboratory setting, dynamic tissue phantoms were developed with tunable parameters that mimic physiologic properties of the skin, including blood vessel volume change, pulse wave frequency, and tissue scattering and absorption. Tissue phantoms were generated using an elastic tubing to represent a blood vessel where the luminal volume could be modulated with a pulsatile fluid flow.

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Burn debridement is a challenging technique that requires significant skill to identify regions requiring excision and appropriate excision depth. A machine learning tool is being developed in order to assist surgeons by providing a quantitative assessment of burn-injured tissue. Three noninvasive optical imaging techniques capable of distinguishing between four kinds of tissue-healthy skin, viable wound bed, deep burn, and shallow burn-during serial burn debridement in a porcine model are presented in this paper.

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Diagnosis and treatment monitoring of cerebrovascular diseases routinely require hemodynamic imaging of the brain. Current methods either only provide part of the desired information or require the injection of multiple exogenous agents. In this study, we developed a multiparametric imaging scheme for the imaging of brain hemodynamics and function using gas-inhalation MRI.

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Burn assessments, including extent and severity, are some of the most critical diagnoses in burn care, and many recently developed imaging techniques may have the potential to improve the accuracy of these evaluations. Optical devices, telemedicine, and high-frequency ultrasound are among the highlights in recent burn imaging advancements. We present another promising technology, multispectral imaging (MSI), which also has the potential to impact current medical practice in burn care, among a variety of other specialties.

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Burn excision, a difficult technique owing to the training required to identify the extent and depth of injury, will benefit from a tool that can cue the surgeon as to where and how much to resect. We explored two rapid and noninvasive optical imaging techniques in their ability to identify burn tissue from the viable wound bed using an animal model of tangential burn excision. Photoplethysmography (PPG) imaging and multispectral imaging (MSI) were used to image the initial, intermediate, and final stages of burn excision of a deep partial-thickness burn.

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Introduction: Multispectral imaging (MSI) is an optical technique that measures specific wavelengths of light reflected from wound site tissue to determine the severity of burn wounds. A rapid MSI device to measure burn depth and guide debridement will improve clinical decision making and diagnoses.

Methodology: We used a porcine burn model to study partial thickness burns of varying severity.

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