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This article reviews existing instruments for measuring emotional intelligence, comparing time-established and popular questionnaires, but it provides no new research findings.

The researchers reported that a new computational method using side-effect data from social media effectively recovers known drug indications and identifies trial indications, suggesting utility for computational drug repositioning.

This study suggests that a novel computational method using side-effect data from social media might aid in drug repositioning by identifying known and potential therapeutic indications.

This study presents a system for evaluating semantic similarity between sentences by using token-based matching and improved similarity measures beyond WordNet.

This study found that a new computational method using side-effect data from social media can successfully identify known and potential new drug indications for repositioning efforts.

This study developed a computational method using side-effect data from social media to identify potential new drug indications, showing that it successfully recovered known and trial indications.

This study introduced an innovative metric for assessing college students' mental health, incorporating temporal perception and a hybrid clustering algorithm, and found it achieved over 90% accuracy, outperforming existing methods in evaluating mental health during public health challenges.

This study suggests that using a new computational method to mine social media for side-effect data may enhance drug repositioning by recovering known and trial drug indications effectively.

This study found that current automatic text generation metrics do not predict human preference judgments for long-form question answering, and suggests adopting a multi-faceted evaluation approach focusing on aspects like factuality and completeness.

This study analyzed Reddit discussions on JAK inhibitors and found that a small number of users contribute most of the conversational content, highlighting the need for expert oversight in interpreting health information shared online.

This study reports on a new semantic annotation approach used to identify substances in MEDLINE abstracts responsible for adverse drug reactions, with promising performance shown by a prototype system.

This study explored how Russian youth aged 18-35 perceive relocation, revealing that attitudes may vary based on stereotypical perceptions of Russia and the USA. The authors used an associative experiment and a psychosemantic approach to identify patterns in these perceptions.

This study found that men receiving negative appearance-related commentary are more likely to experience negative psychological outcomes, while positive feedback tends to lead to better outcomes despite encouraging appearance-change behaviors.

This study highlights challenges in evaluating long-form question answering, suggesting that current automated metrics do not align with human judgments, and it advocates for a multi-faceted evaluation approach.

This study introduces scINSIGHT, a method that showed improved performance over existing approaches in identifying gene expression patterns and cellular processes in heterogeneous scRNA-seq datasets from different biological conditions.

This study introduces scINSIGHT, a method to analyze single-cell RNA sequencing data that outperforms existing techniques in identifying gene expression patterns across different biological conditions.

This study describes an AI-powered system for diagnosing dermatological conditions, achieving a weighted score of 0.87 in both contextual understanding and diagnostic accuracy, suggesting it could enhance tele-dermatology applications by supporting remote consultations and care access in underserved regions.

This study interpreted McDonald's Father's Day advertising posters using semiotic analysis, finding that the imagery and text symbolically represent a father figure and McDonald's branding to celebrate the occasion.

This study describes a computational method using side-effect data from social media to identify new drug indications, suggesting it could be effective for drug repositioning.

This paper explores how the immunological responses of breast cancer patients are transformed into an economic process by commoditizing treatment-related needs, documenting this journey through an ethnographic study with a breast cancer charity.

This study found that a five-dimensional model of personality perception from men's facial photographs better captures the complexity of face perception than the traditional two-dimensional Valence-Dominance model, highlighting overlaps with personality structures known from differential psychology.

This article introduces signatureSearch, a software package designed for gene expression signature searching and functional enrichment analysis, but reports no new clinical results.

This study explored social media users' attitudes towards cosmetic and lifestyle products, revealing mixed perceptions, including positive views on rosemary and Sudocream for certain benefits, but also negative experiences like hair loss and worsening acne.

This study found that gaze duration in a social evaluation task was linked to mental health outcomes in trans men, trans women, and cisgender women more than six months later.

The digital system for measuring melasma shows promise but needs more development for better accuracy and automation.

In this study, the authors found that syntax-based neural networks performed comparably to pre-trained Transformers on tasks involving definitely unseen sentences, suggesting they are a more transparent and parameter-efficient alternative for certain Natural Language Processing applications.

This study found that the most significant negative emotional responses among cancer patients during consultations were related to treatment delays and the possibility of hair loss.

This study surveyed university students in ten Eastern European and Central Asian countries to assess their attitudes toward individuals using wheelchairs, finding generally neutral or negative attitudes, though Ukrainian students affected by conflict displayed more positive views.

This article presents a computer imaging algorithm that may automate and enhance the Severity of Alopecia Tool scoring for alopecia areata through texture analysis of pediatric images.