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Artificial intelligence and machine learning applications are emerging as transformative technologies in medicine. With greater access to a diverse range of big datasets, researchers are turning to these powerful techniques for data analysis. Machine learning can reveal patterns and interactions between variables in large and complex datasets more accurately and efficiently than traditional statistical methods. Machine learning approaches open new possibilities for studying SLE, a multifactorial, highly heterogeneous and complex disease. Here, we discuss how machine learning methods are rapidly being integrated into the field of SLE research. Recent reports have focused on building prediction models and/or identifying novel biomarkers using both supervised and unsupervised techniques for understanding disease pathogenesis, early diagnosis and prognosis of disease. In this review, we will provide an overview of machine learning techniques to discuss current gaps, challenges and opportunities for SLE studies. External validation of most prediction models is still needed before clinical adoption. Utilisation of deep learning models, access to alternative sources of health data and increased awareness of the ethics, governance and regulations surrounding the use of artificial intelligence in medicine will help propel this exciting field forward.

Cell migration is the major driver of invasion and metastasis during cancer progression. For cells to migrate, they utilize the actin–myosin cytoskeleton and adhesion molecules, such as integrins and CD44, to generate traction forces in their environment. CD44 primarily binds to hyaluronic acid (HA) and integrins primarily bind to extracellular matrix (ECM) proteins such as collagen. However, the role of CD44 under integrin-mediated conditions and vice versa is not well known. Here, we performed traction force microscopy (TFM) on U251 cells seeded on collagen I-coated polyacrylamide gels to assess the functional mechanical relationship between integrins and CD44. Performing TFM on integrin-mediated adhesion conditions, i.e., collagen, we found that CD44KO U251 cells exerted more traction force than wild-type (WT) U251 cells. Furthermore, untreated WT and CD44-blocked WT exhibited comparable results. Conversely, in CD44-mediated adhesive conditions, integrin-blocked WT cells exerted a higher traction force than untreated WT cells. Our data suggest that CD44 and integrins have a mutually antagonistic relationship where one receptor represses the other's ability to generate traction force on its cognate substrate. [ABSTRACT FROM AUTHOR]

Objective: Age‐related hearing loss (ARHL) is a prevalent but often underdiagnosed and undertreated condition among individuals aged 50 and above. It is associated with various sociodemographic factors and health risks including dementia, depression, cardiovascular disease, and falls. While the causes of ARHL and its downstream effects are well defined, there is a lack of priority placed by clinicians as well as guidance regarding the identification, education, and management of this condition. Purpose: The purpose of this clinical practice guideline is to identify quality improvement opportunities and provide clinicians trustworthy, evidence‐based recommendations regarding the identification and management of ARHL. These opportunities are communicated through clear actionable statements with explanation of the support in the literature, evaluation of the quality of the evidence, and recommendations on implementation. The target patients for the guideline are any individuals aged 50 years and older. The target audience is all clinicians in all care settings. This guideline is intended to focus on evidence‐based quality improvement opportunities judged most important by the guideline development group (GDG). It is not intended to be a comprehensive, general guide regarding the management of ARHL. The statements in this guideline are not intended to limit or restrict care provided by clinicians based on their experience and assessment of individual patients. Action Statements: The GDG made strong recommendations for the following key action statements (KASs): (KAS 4) If screening suggests hearing loss, clinicians should obtain or refer to a clinician who can obtain an audiogram. (KAS 8) Clinicians should offer, or refer to a clinician who can offer, appropriately fit amplification to patients with ARHL. (KAS 9) Clinicians should refer patients for an evaluation of cochlear implantation candidacy when patients have appropriately fit amplification and persistent hearing difficulty with poor speech understanding. The GDG made recommendations for the following KASs: (KAS 1) Clinicians should screen patients aged 50 years and older for hearing loss at the time of a health care encounter. (KAS 2) If screening suggests hearing loss, clinicians should examine the ear canal and tympanic membrane with otoscopy or refer to a clinician who can examine the ears for cerumen impaction, infection, or other abnormalities. (KAS 3) If screening suggests hearing loss, clinicians should identify sociodemographic factors and patient preferences that influence access to and utilization of hearing health care. (KAS 5) Clinicians should evaluate and treat or refer to a clinician who can evaluate and treat patients with significant asymmetric hearing loss, conductive or mixed hearing loss, or poor word recognition on diagnostic testing. (KAS 6) Clinicians should educate and counsel patients with hearing loss and their family/care partner(s) about the impact of hearing loss on their communication, safety, function, cognition, and quality of life (QOL). (KAS 7) Clinicians should counsel patients with hearing loss on communication strategies and assistive listening devices. (KAS 10) For patients with hearing loss, clinicians should assess if communication goals have been met and if there has been improvement in hearing‐related QOL at a subsequent health care encounter or within 1 year. The GDG offered the following KAS as an option: (KAS 11) Clinicians should assess hearing at least every 3 years in patients with known hearing loss or with reported concern for changes in hearing. [ABSTRACT FROM AUTHOR]

Liposarcomas are the most common soft tissue sarcoma in adults, whereas liposarcomas of the head and neck, particularly the hypopharynx, are incredibly rare - with approximately 50 cases reported in the literature. We present a case of an otherwise healthy and asymptomatic 42-year-old male who presented dramatically after vomiting up a large soft tissue mass. The lesion was surgically removed via transoral approach with blue laser, and diagnosis of well-differentiated liposarcoma was made via MDM2 gene amplification by FISH. Oral extrusion is a rare feature of this disease. This is the first documented case of an orally extruded liposarcoma to present in an otherwise asymptomatic and healthy patient, demonstrating how this entity may be indolent until initial presentation. Laryngoscope, 134:4688-4690, 2024., (© 2024 The Author(s). The Laryngoscope published by Wiley Periodicals LLC on behalf of The American Laryngological, Rhinological and Otological Society, Inc.)

Objectives: Hispanic/Latino adults are less likely than non-Hispanic White adults to seek treatment for hearing disability. While differential socioeconomic factors may contribute to this finding, differences in phonology and syntax in the Spanish, versus English, language may also influence patient perception of hearing disability. The objective of this study is to investigate the association between primary language spoken and participant perception of hearing disability., Design: This study represents a cross-sectional cohort study using National Health and Nutrition Examination Study cycles 2015-2016 and 2017-2020 data. Multivariable logistic regressions estimated the association between respondent-selected interview language, which was used as a proxy for primary spoken language, and participant perception of hearing disability. Models were adjusted for age, gender, highest degree of education, pure-tone average, and self-reported general health. Participants included 4687 individuals from the United States population who elected to speak English (n = 4083) or Spanish (n = 604) during the interview. Perception of hearing disability was assessed by (1) frequency of reported difficulty in following a conversation in noise, (2) frequency with which hearing caused respondents to experience frustration when talking with members of their family or friends, and (3) participants' subjective overall assessment of their hearing., Results: Speaking Spanish, versus English, as a primary language was associated with a 42% lower odds of reporting difficulty hearing and understanding in background noise (odds ratio [OR]: 0.58, 95% confidence interval [CI]: 0.48 to 0.70). Spanish speakers had 28% lower odds of reporting feeling frustrated when talking to family members or friends due to hearing (OR: 0.72, 95% CI: 0.59 to 0.88) as compared with the English-speaking cohort. Speaking Spanish additionally conferred 31% lower odds of describing their own general hearing as "a little trouble to deaf" than participants speaking English (OR: 0.69, 95% CI: 0.53 to 0.90). These observed associations were independent of age, gender, highest degree of education, better pure-tone average? and self-reported general health., Conclusions: Primary Spanish speakers may be less likely than English speakers to report hearing-related disability, an effect which may be independent of ethnicity. Patient perception of hearing-related disability is an important component of the assessment of and counseling for hearing-related disability and discussion of the need for amplification or other hearing intervention., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: This study investigated the comparative performance of ear, nose, and throat (ENT) physicians in correctly detecting ear abnormalities when reviewing digital otoscopy imaging using 3 different visualization methods, including computer-assisted composite images called "SelectStitch," single video frame "Still" images, and video clips. The study also explored clinicians' diagnostic confidence levels and the time to make a diagnosis., Study Design: Clinician diagnostic reader study., Setting: Online diagnostic survey of ENT physicians., Methods: Nine ENT physicians reviewed digital otoscopy examinations from 86 ears with various diagnoses (normal, perforation, retraction, middle ear effusion, tympanosclerosis). Otoscopy examinations used artificial-intelligence (AI)-based computer-aided composite image generation from a video clip (SelectStitch), manually selected best still frame from a video clip (Still), or the entire video clip. Statistical analyses included comparisons of ability to detect correct diagnosis, confidence levels, and diagnosis times., Results: The ENT physicians' ability to detect ear abnormalities (33.2%-68.7%) varied depending on the pathologies. SelectStitch and Still images were not statistically different in detecting abnormalities (P > .50), but both were different from Video (P < .01). However, the performance improvement observed with Videos came at the cost of significantly longer time to determining the diagnosis. The level of confidence in the diagnosis was positively associated with correct diagnoses, but varied by particular pathology., Conclusion: This study explores the potential of computer-assisted techniques like SelectStitch in enhancing otoscopic diagnoses and time-saving, which could benefit telemedicine settings. Comparable performance between computer-generated and manually selected images suggests the potential of AI algorithms for otoscopy applications., (© 2024 American Academy of Otolaryngology–Head and Neck Surgery Foundation.)