AstraZeneca’s hyperkalaemia drug Lokelma could see its use by the NHS more than double thanks to updated guidance from NICE.
Ideaya’s uveal melanoma drug exceeds success benchmark in late-stage trial
Ideaya’s late-stage data for a rare eye cancer drug has passed the company’s benchmark for success, bolstering expectations for a planned accelerated filing in the US. The open-label Phase 2/3 uveal melanoma trial tested the …
Data backs GSK’s ovarian cancer blockbuster hopes
GSK’s B7-H4-targeting ADC Mo-Rez chalks up impressive results in ovarian and endometrial cancer, prompting a major phase 3 trials programme.
FDA hands another rejection to Replimune’s melanoma therapy
Replimune has had its advanced melanoma treatment RP1 turned down by the FDA for a second time, prompting job losses.
ViiV launches ‘Still Here’ campaign aimed at reminding younger people about HIV
GSK and Shionogi’s ViiV Healthcare is seeking to raise awareness around what the company sees as a forgotten element in HIV: younger people with the infection.
Assessing nurses’ attitudes toward artificial intelligence in Kazakhstan: psychometric validation of a nine-item scale
BackgroundArtificial intelligence (AI) is increasingly integrated into healthcare, yet the attitudes and knowledge of nurses, who are the key mediators of AI implementation, remain underexplored. This study aimed to evaluate the psychometric properties of a previously validated nine-item scale measuring nurses’ knowledge and attitudes toward AI and to describe preliminary findings from primary healthcare centre […]
A review for navigating the trade-offs: evaluating open-source and proprietary large language models for clinical and biomedical information extraction
The exponential growth of biomedical data necessitates advanced tools for efficient information extraction (IE) to support clinical decision-making and research. Large language models (LLMs) have emerged as transformative solutions, yet their application in healthcare raises critical trade-offs between open-source (OSS) and proprietary models. This review evaluates IE workflows such as named entity recognition, relation extraction, […]
From memorization to generalization: fine-tuning large language models for biomedical term-to-identifier normalization
IntroductionBiomedical data integration requires term-to-identifier normalization, the process of linking natural-language biomedical terms to standardized ontology codes so that extracted concepts become computable and interoperable. Although large language models perform well on clinical text summarization and concept extraction, they remain markedly less accurate at mapping ontology terms to their corresponding identifiers.MethodsWe examined the roles of […]
Structuring medication safety narratives: development and evaluation of the medication-related incident reports annotation scheme
IntroductionNarrative reports of medication-related incidents contain valuable information about the causes and consequences of errors, but their unstructured format limits systematic analysis. Although natural language processing (NLP) can convert narrative reports into structured data, few annotation schemes have been developed specifically for medication safety and validated using real-world healthcare incident data. This study aimed to […]
Use of digital patients in clinical simulation for nursing education: a scoping review protocol
IntroductionClinical simulation represents an emerging educational technology delivered through software-based platforms, accessible via computers or head-mounted displays. It is characterized as a partially immersive, screen-mediated experience in which learners are placed in simulated roles that require the execution of psychomotor actions, clinical decision-making, and interpersonal communication skills.Methods and analysisThis scoping review protocol follows the methodological […]
Deep learning for intracranial hemorrhage detection and classification in brain CT scans: a systematic review and hybrid model approach
BackgroundIntracranial hemorrhage (ICH) is a life-threatening medical emergency requiring rapid and accurate diagnosis. Non-contrast computed tomography (CT) remains the primary imaging modality for detecting acute hemorrhage. In recent years, machine learning (ML) and deep learning (DL) approaches have gained increasing attention for automated detection and classification of ICH and its subtypes. This systematic review aims […]
IoT-based health monitoring and social welfare access for Thailand’s older adults
IntroductionThailand’s population is shifting, with 20% aged 60 and over in 2022, leading to healthcare and social welfare challenges. Digital technologies, particularly those using IoT, may improve health outcomes for older adults but face hurdles due to low digital literacy and a digital divide between urban and rural areas. This study investigated the accessibility and […]