Search

everythingexperts & clinicslearnfaqsresearchcommunity

for

Search:↓

In this study, researchers implemented a recommendation algorithm using Melia dubia liquid and fermented rice water to improve nutritional suggestions for women experiencing menstrual issues, achieving an accuracy of 94% in detecting nutritional needs during menstrual cycles.

This study demonstrates that combining gene expression data with a random forest algorithm provides highly accurate diagnosis of childhood growth hormone deficiency, showing potential utility in distinguishing it from non-GHD short stature.

In this study, tubular 3D bioprinted structures made from sodium alginate and gelatin, containing NIH/3T3 fibroblast cells, demonstrated the ability for cell growth and network formation over 6 weeks, although structural tensile strength decreased with cell growth and polymer degradation.

This study observed that a peptide showed higher antioxidant and metal ion chelation activity compared to its encapsulated version cross-linked in calcium alginate beads.

This article reviews strategies for serological testing in diagnosing ILD linked to systemic rheumatic diseases and introduces a potential diagnostic algorithm for pulmonologists, while noting further validation is needed.

This review discusses the increasing role of machine learning in drug repurposing, demonstrating how algorithms can reveal new therapeutic uses for existing drugs and predict side effects, with potential benefits for precision medicine, while also addressing ethical and privacy concerns.

In this study, a machine learning framework incorporating the CatBoost algorithm accurately predicted Systemic Lupus Erythematosus in Omani patients, suggesting potential for early clinical intervention.

This article provides a review of alopecia areata, highlighting the development of diagnostic and therapeutic algorithms that consider factors such as age, disease severity, and quality of life, but it reports no new clinical findings.

This article reviews differential diagnosis approaches for 46,XY DSD, proposing a diagnostic algorithm focused on biochemical and genetic data, without presenting new clinical results.

In this study, researchers developed a microfluidics-based method for creating uniform, size-controlled stem cell spheroids that enhance osteogenic differentiation when encapsulated in alginate-RGD microgels.

In this study, researchers used genetic data from over 52,000 men to identify over 250 genetic loci associated with severe hair loss and developed a predictive algorithm for determining hair loss risk.

This study observed that while TikTok offers the best flow for videos on laryngeal cancer, YouTube provides higher quality, but video quality overall needs professional enhancement and platform algorithm improvements.

This article reviews treatment options for male-pattern and female-pattern hair loss, telogen effluvium, and alopecia areata, but provides no new clinical results; algorithmic management approaches are included.

This study used machine learning models to analyze PCOS symptoms for early diagnosis, finding Support Vector Machine and VGG16 algorithms achieved high accuracy rates of 94.44% and 98.29% respectively.

This review discusses various treatment options for alopecia areata tailored by age and severity, providing a practical algorithm, but reports no new clinical results.

This review discusses the characteristics, extraction strategies, and potential applications of plant and algal lipid droplets but reports no new empirical findings.

This review discusses the clinical guidelines for hidradenitis suppurativa, detailing its definition, impacts, and treatments, and includes a proposed therapeutic approach algorithm, but reports no new clinical findings.

In a comparative genomic study, researchers observed significant genetic differences among the three chemical races of the alga Botryococcus braunii, leading them to propose reclassifying these races as distinct species based on their unique genomic characteristics.

This study analyzed deep learning's application to automate hair density measurement in images and found that YOLOv4 had the best performance among tested algorithms, with a mean average precision of 58.67.

This review discusses various treatment options for alopecia areata, noting a lack of consensus on grading and treatment algorithms, and reports no new clinical results.

In this study, researchers developed a predictive model for the onset of alopecia areata by analyzing six datasets to identify key feature genes and employing various machine learning algorithms, ultimately finding the XGBoost model most effective for clinical application.

This chapter discusses common endocrine disorders affecting the pituitary, thyroid, and adrenal glands, and their impact on human fertility, emphasizing practical evaluation and treatment algorithms.

This review highlights the challenges and management strategies associated with persistent chemotherapy-induced alopecia, detailing the psychosocial impacts, follicular pathobiology, and available treatments such as scalp cooling and minoxidil, ultimately proposing a clinical algorithm to transform it into a preventable and manageable condition.

This systematic review identified and evaluated the most accurate ICD code classification methods for dermatologic conditions in US-based datasets, highlighting both high-performing algorithms and areas lacking validation, thereby informing future research and dataset use.

This study introduces a novel image enhancement method that significantly improves the visual quality of low-light sports images by utilizing improved bilateral filtering and the CLAHE algorithm, achieving a 65.24% improvement in color and edge detail preservation compared to state-of-the-art methods on the LOL dataset.

This study reviews AI's role in aesthetic medicine, noting it enhances diagnostic accuracy and personalized treatment planning, but faces challenges like ethical concerns, algorithmic biases, and regulatory issues that need addressing for successful integration.

This case report suggests the co-occurrence of systemic lupus erythematosus and an eating disorder in an adolescent may be linked through shared adolescent stress factors rather than neuropsychiatric lupus, despite algorithmic indications.

This abstract highlights the prevalence of androgenetic alopecia in men and young adults and mentions the psychological impact, noting that while various therapies exist, clear treatment algorithms are lacking according to this source.

In this study, researchers at the Laboratory of Regenerative Medicine WUM are exploring the long-term effects of SARS-CoV-19 infection, focusing on stem cell mobilization and engraftment processes, and utilizing advanced diagnostic techniques to develop algorithms for rare disease classification, including amyloidosis.

This study found that low image resolutions allow expert clinicians to detect alopecia, but higher resolutions are necessary for identifying scarring and vellus hair, which may inform future image processing algorithms in dermatology.