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SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We report here the benefits of using SpliceAI-visual and demonstrate its relevance in the assessment/modulation of the PVS1 classification criteria. We also show how SpliceAI-visual can elucidate several complex splicing defects taken from the literature but also from unpublished cases. SpliceAI-visual is available as a Google Colab notebook and has also been fully integrated in a free online variant interpretation tool, MobiDetails ( https://mobidetails.iurc.montp.inserm.fr/MD ).
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http://dx.doi.org/10.1186/s40246-023-00451-1 | DOI Listing |
BMJ Open
September 2025
Pharmacy Department, St John of God University Hospital, Dublin, Ireland.
Objectives: To address the lack of accurate and accessible mental health medicines-information resources for children, young people and their parents/guardians using design thinking to co-design free-to-use, video resources tailored to this audience.
Design: A multiphase qualitative case study using the Double Diamond model of Design Thinking: Discover, Define, Develop and Deliver. This included iterative prototyping, thematic analysis and public and patient involvement throughout.
JMIR Cancer
September 2025
Cancer Patients Europe, Rue de l'Industrie 24, Brussels, 1000, Belgium.
Background: Breast cancer is the most common cancer among women and a leading cause of mortality in Europe. Early detection through screening reduces mortality, yet participation in mammography-based programs remains suboptimal due to discomfort, radiation exposure, and accessibility issues. Thermography, particularly when driven by artificial intelligence (AI), is being explored as a noninvasive, radiation-free alternative.
View Article and Find Full Text PDFJ Palliat Med
September 2025
ATLANTES Global Observatory of Palliative Care, Instituto Cultura y Sociedad, Universidad de Navarra, Navarra, Spain.
International research projects, such as Horizon 2020 (H2020) and ERASMUS+, generate numerous scientific and educational outcomes. However, these are often disseminated in fragmented formats, limiting long-term access and impact. Language barriers further complicate the dissemination in professional communities that do not speak English.
View Article and Find Full Text PDFAnn Surg Oncol
September 2025
Department of Hepatobiliary Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai, China.
Background: Postoperative late recurrence (POLAR) after 2 years from the date of surgical resection of hepatocellular carcinoma (HCC) represents a unique surveillance and management challenge. Despite identified risk factors, individualized prediction tools to guide personalized surveillance strategies for recurrence remain scarce. The current study sought to develop a predictive model for late recurrence among patients undergoing HCC resection.
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