Background The use of artificial intelligence (AI) algorithms for the diagnosis of skin diseases has shown promise in experimental settings but has not been yet tested in real‐life conditions. Objective To assess the diagnostic performance and potential clinical utility of a 174‐multiclass AI algorithm in a real‐life telemedicine setting. Methods Prospective, diagnostic accuracy study including consecutive patients who submitted images for teledermatology evaluation. The treating dermatologist chose a single image to upload to a web application during teleconsultation. A follow‐up reader study including nine healthcare providers (3 dermatologists, 3 dermatology residents and 3 general practitioners) was performed. Results A total of 340 cases from 281 patients met study inclusion criteria. The mean (SD) age of patients was 33.7 (17.5) years; 63% (n = 177) were female. Exposure to the AI algorithm results was considered useful in 11.8% of visits (n = 40) and the teledermatologist correctly modified the real‐time diagnosis in 0.6% (n = 2) of cases. The overall top‐1 accuracy of the algorithm (41.2%) was lower than that of the dermatologists (60.1%), residents (57.8%) and general practitioners (49.3%) (all comparisons P < 0.05, in the reader study). When the analysis was limited to the diagnoses on which the algorithm had been explicitly trained, the balanced top‐1 accuracy of the algorithm (47.6%) was comparable to the dermatologists (49.7%) and residents (47.7%) but superior to the general practitioners (39.7%; P = 0.049). Algorithm performance was associated with patient skin type and image quality. Conclusions A 174‐disease class AI algorithm appears to be a promising tool in the triage and evaluation of lesions with patient‐taken photographs via telemedicine.

The period-change rate (PCR) of pulsating variable stars is a useful probe of changes in their interior structure, and thus of their evolutionary stages. So far, the PCRs of Classical Cepheids in the Large Magellanic Cloud (LMC) have been explored in a limited sample of the total population of these variables. Here we use a template-based method to build observed minus computed (O − C) period diagrams, from which we can derive PCRs for these stars by taking advantage of the long time baseline afforded by the Digital Access to a Sky Century @ Harvard (DASCH) light curves, combined with additional data from the Optical Gravitational Lensing Experiment (OGLE), the MAssive Compact Halo Object (MACHO) project, Gaia’s Data Release 2, and in some cases the All-Sky Automated Survey (ASAS). From an initial sample of 2315 sources, our method provides an unprecedented sample of 1303 LMC Classical Cepheids with accurate PCRs, the largest for any single galaxy, including the Milky Way. The derived PCRs are largely compatible with theoretically expected values, as computed by our team using the Modules for Experiments in Stellar Astrophysics (MESA) code, as well as with similar previous computations available in the literature. Additionally, five long-period ($P&gt;50\, \rm {d}$) sources display a cyclic behaviour in their O − C diagrams, which is clearly incompatible with evolutionary changes. Finally, on the basis of their large positive PCR values, two first-crossing Cepheid candidates are identified.

Liposuction is a common aesthetic procedure; however, to date, liposuction has not been linked to morphea. The aim was to review cases with a history of liposuction that presented active morphea lesions in the same surgery regions and were confirmed by ultrasound and histology. A retrospective descriptive analysis of the clinical, ultrasonographic, and pathology database took place (2014)(2015)(2016)(2017)(2018)(2019)(2020). Eleven patients met the criteria. Ultrasound supported the diagnosis, and the ultrasonographic signs of activity in these cases matched the features described in the literature in 100% of cases. In summary, morphea may appear after liposuction and ultrasound can support its early detection.

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Pulsating stars, such as Cepheids and RR Lyrae, offer us a window to measure and study changes due to stellar evolution. In this work, we study the former by calculating a set of evolutionary tracks of stars with an initial mass of 4 to 7 M⊙, varying the initial rotation rate and metallicity, using the stellar evolution code Modules for Experiments in Stellar Astrophysics (MESA). Using Radial Stellar Pulsations (RSP), a recently added functionality of MESA, we obtained theoretical instability strip (IS) edges and linear periods for the radial fundamental mode. Period-age, period-age-temperature, period-luminosity, and period-luminosity-temperature relationships were derived for three rotation rates and metallicities, showing a dependence on crossing number, position in the IS, rotation, and metallicity. We calculated period change rates (PCRs) based on the linear periods from RSP. We compared our models with literature results using the Geneva code, and found large differences, as expected due to the different implementations of rotation between codes. In addition, we compared our theoretical PCRs with those measured in our recent work for Large Magellanic Cloud Cepheids. We found good overall agreement, even though our models do not reach the short-period regime exhibited by the empirical data. Implementations of physical processes not yet included in our models, such as pulsation-driven mass loss, an improved treatment of convection that may lead to a better description of the instability strip edges, as well as consideration of a wider initial mass range, could all help improve the agreement with the observed PCRs.