1288 published stories · page 5 of 86
An inappropriate video of Devara: Part 1 stars Jr NTR and Janhvi Kapoor from the film's song Chuttamalle went viral on social media.
Hindustan Times
Healthcare communication faces unprecedented challenges as the healthcare workforce is increasingly faced with increased administrative burdens and reduced time with patients. Conversational agents powered by generative AI may offer a potential solution by collecting information, answering questions, documenting encounters, and supporting clinical decision-making through fluid, contextual dialogue. However, realizing their potential requires rigorous validation, careful implementation, and a strong commitment to…
Background The albumin-bilirubin (ALBI) score, an objective liver function and prognostic indicator, has shown predictive value in various diseases, but its long-term prognostic significance in stroke survivors remains unclear. Objective To evaluate the ALBI score's predictive value for all-cause mortality (ACM) in individuals with stroke. Methods Data from the National Health and Nutrition Examination Survey (1999-2018) were analyzed. The Boruta algorithm selected key variables associated with ACM. Kaplan-Meier…
Objectives To evaluate the diagnostic accuracy of a publicly available DenseNet-121 convolutional neural network (TorchXRayVision) for triaging chest radiographs of health assessment applicants at a tertiary hospital in Nepal. Design Prospective, single-centre, shadow-mode diagnostic accuracy validation study. Reported in accordance with the Standards for Reporting of Diagnostic Accuracy Studies (STARD) 2015 checklist and STARD-Artificial Intelligence (AI)/Developmental and Exploratory Clinical Investigations of…
Acute myeloid leukemia (AML) is a hematologic malignancy in which accurate subtype identification is important for treatment planning and prognosis. This study developed a deep learning approach for AML subtype classification using multiple single-cell images from each patient rather than conventional instance-based classification. An open-source dataset containing 81,214 single-cell images from 189 individuals was analyzed. The dataset included four genetically defined AML subtypes and a healthy control group.…
Premise Herbarium specimens represent critical historical records of plant phenology, yet automating annotation of reproductive structures remains challenging given the diversity of floral morphologies, specimen age and quality, and image quality. Methods Here, we present a machine learning pipeline that uses an ensemble modeling approach to detect flowers on herbarium specimens and deliver these data to the phenology research community. After testing multiple strategies for generating training data, we found th…
Background The growing integration of artificial intelligence (AI) in healthcare necessitates that nurse leaders develop advanced competencies in decision-making, communication, and data-informed clinical judgment. Traditional simulation-based education, while effective, often relies on fixed scenarios with limited adaptability and minimal real-time decision support. AI-enhanced simulation offers a potential solution by creating responsive, adaptive learning environments that support leadership development. Meth…
Background Oral potentially malignant disorders (OPMDs) are precursors to oral squamous cell carcinoma (OSCC), a malignancy with high morbidity and mortality due to late diagnosis. Conventional diagnostic methods, though accurate, are invasive and often inaccessible in resource-limited areas. Intraoral mobile photographs integrated with artificial intelligence (AI) as a screening tool may offer a noninvasive, cost-effective, and accessible alternative for early detection of OPMDs. The study aimed to evaluate the…
Objectives To produce the first structured longitudinal dataset of symptom severity trajectories in vagus nerve stimulation (VNS) patients using a 2-stage large language model pipeline for automated symptom severity extraction from clinical notes, as part of the NIH-funded research evaluating vagal excitations and anatomical linkages (U54AT012307). Materials and methods We analyzed 1427 annotated clinical notes from 95 patients across 5 corpora. LLaMA models (3.2-1B, 3.2-3B, and 3.3-70B) were fine-tuned to class…
Digital orthopedics integrates artificial intelligence, finite element analysis, virtual surgical planning, intraoperative navigation, robotics, and three-dimensional printing into a precise, individualized workflow for scaphoid fracture management. Artificial intelligence-based algorithms achieve high diagnostic accuracy for scaphoid fractures on plain radiographs, aid in detecting occult fractures, and support treatment decisions. Three-dimensional fracture mapping and finite element analysis enable quantitati…
Free-space optical communications systems offer high bandwidth, increased security and license-free operation but are highly affected by the performance degradation due to the atmospheric attenuation caused by scattering and absorption. The prediction of attenuation accuracy is even more important in Iraq where the environment is hot, dusty, foggy and rainy in a random fashion. The aim of this study is to assess the performance of machine learning, deep learning and hybrid modeling techniques for the prediction…
As artificial intelligence (AI) expands across mental health services, questions arise about whether it can replace digital health navigators (DHNs), including those with lived experience. The DHN role generally resists automation because lived experience deepens specific dimensions that AI cannot replicate. Drawing on emerging evidence of AI's limitations in contextual reasoning, cultural sensitivity, and clinical safety, the authors identify where DHNs with lived experience are least substitutable: real-world…
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