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PubMed1999

New paradigms for medical decision support and education: the Stanford Health Information Network for Education.

The information needs of physicians are complex and ever increasing in a world of rapidly expanding medical knowledge and a practice environment where physicians are required to know and do more with shrinking resources. Current strategies for providing clinical decision support and continuing medical education have failed, in part, because they have not provided timely, easy access to information that is current, integrated with other information and the physician's workflow, and relevant to specific questions that occur during the patient encounter. Meeting these challenges involves understanding the nature of medical knowledge, the different information needs of physicians, the clinical decision-making process, and the constraints of the physicians work environment, as well as the traditional barriers to physician education. We explore the nature of some of these challenges and propose one solution in the form of a highly integrated web-based technology--The Stanford Health Information Network for Education.

Academic Medical Centers↗
PubMed2026

Artificial intelligence for translational personalized neoantigen cancer vaccine development.

Personalized neoantigen cancer vaccine is a promising strategy for precision immunotherapy by targeting patient-specific and mutation-derived tumor antigens. Early clinical studies have demonstrated the feasibility, safety, and immunogenicity of these vaccines across multiple solid tumors, with encouraging outcomes particularly when combined with immune checkpoint blockade. However, broader clinical translation remains limited by sequential bottlenecks across the vaccine development pipeline, including false-positive neoantigen selection,  imperfect modeling of antigen processing and HLA presentation, limited prediction of T-cell receptor recognition, and challenges in formulation, delivery, and manufacturing. Artificial intelligence and advanced computational workflows are increasingly integrated into this pipeline to improve candidate prioritization and support more reproducible decision-making. In this review, we summarize clinical progress and key translational barriers in personalized neoantigen vaccination, and discuss how AI-enabled approaches may contribute across four major stages: multi-omics integration for neoantigen discovery, processing-aware HLA presentation prediction, structure-aware and TCR-informed immunogenicity modeling, and data-driven formulation optimization, particularly for lipid nanoparticle-based delivery systems. These approaches are able to help narrow biological and chemical search spaces, improve prioritization, and provide mechanistic insights into antigen presentation and immune recognition rather than replacing experimental validation. This articlefurther addresses future implementation challenges, including dataset diversity, model interpretability, prospective benchmarking, manufacturing traceability, and evolving regulatory frameworks for individualized mRNA cancer immunotherapies. Integrating computational innovation with rigorous immunological validation, scalable manufacturing, and regulatory oversight will be essential for advancing personalized neoantigen vaccines toward broader clinical implementation.

Cancer Vaccines↗
PubMed2026

A Simplified Workflow for the Prediction of Putative Viral Reads Using NIPT Data.

OBJECTIVE: Non-invasive prenatal testing (NIPT) identifies fetal chromosomal abnormalities by sequencing cell-free fetal DNA (cffDNA). Recent studies suggest the prediction of viral sequences from NIPT data, but current methods lack cost-effectiveness for routine use. This study develops a straightforward workflow to investigate potential viral signatures in pregnant women using NIPT data from 888 Iranian participants. METHOD: Two bioinformatic workflows were compared for predicting viral reads: the traditional method involved mapping reads to the human genome, followed by mapping unmapped reads to viral references, and a direct mapping approach to viral genomes, as proposed in this research. RESULTS: While maintaining reproducibility comparable to the conventional method, the proposed workflow minimizes computational complexity and time usage for data processing. Ultimately, this analysis suggested viral DNA in 24.2% of samples, encompassing 29 distinct species, implying the diversity of the maternal virome. CONCLUSION: This study presents a computationally efficient workflow for the in silico prediction of viral-like sequences from routine NIPT data. Further experimental validation is essential to verify the presence, viability, or clinical relevance of these sequences.

Humans↗
PubMed2026

Multi-omic analyses of the same sample using metabolomics, lipidomics, proteomics, phosphoproteomics, and glycoproteomics.

Mass spectrometry (MS)-based multi-omics offers powerful tools to comprehensively characterize proteins, post-translational modifications, metabolites, and lipids. However, these measurements are typically performed using separate sample preparation workflows and modality-specific liquid chromatography mass spectrometry (LC-MS) platforms, limiting integration and constraining applications to small amounts of sample materials, especially scarce clinical specimens. Here, we describe a unified nano-LC-MS framework that enables metabolomic, lipidomic, proteomic, phosphoproteomic, and glycoproteomic analyses from the same starting material using a single nano-LC-MS platform, with only the chromatographic conditions, acquisition methods, and enrichment procedures tailored to each omics. This integrated strategy reduces workflow complexity and sample consumption while improves analytical continuity across molecular layers. By enabling deep multi-omics characterization from the same sample, this platform provides a practical foundation for comprehensive analysis of precious clinical samples.

Proteomics↗
PubMed2004

The impact of automation on organizational changes in a community hospital clinical microbiology laboratory.

The diagnosis of infectious diseases and the role of the microbiology laboratory are currently undergoing a process of change. The need for overall efficiency in providing results is now given the same importance as accuracy. This means that laboratories must be able to produce quality results in less time with the capacity to interpret the results clinically. To improve the clinical impact of microbiology results, the new challenge facing the microbiologist has become one of process management instead of pure analysis. A proper project management process designed to improve workflow, reduce analytical time, and provide the same high quality results without losing valuable time treating the patient, has become essential. Our objective was to study the impact of introducing automation and computerization into the microbiology laboratory, and the reorganization of the laboratory workflow, i.e. scheduling personnel to work shifts covering both the entire day and the entire week. In our laboratory, the introduction of automation and computerization, as well as the reorganization of personnel, thus the workflow itself, has resulted in an improvement in response time and greater efficiency in diagnostic procedures.

Automation↗
PubMed2026

Optimizing GRIDSS for clinical use: A targeted NGS filtering strategy for germline structural variant detection.

Detecting intermediate-sized structural variants (SVs) remains challenging in diagnostics, as tools for single-nucleotide and copy-number variants, particularly read-depth-based methods, are often insufficient. GRIDSS addresses this gap by integrating paired-end mapping, split-read analysis, and assembly-based approaches. However, its use in targeted sequencing and diagnostic workflows remains complex. NGS panel data from 9726 patients with suspected hereditary cancer were analyzed using GRIDSS. A filtering strategy was developed to prioritize clinically relevant germline SVs. Multiple parameter settings were tested to optimize performance. The initial dataset of 1,307,592 variants was reduced to 89 candidates after applying the selected filtering strategy. Of these, 24 had been previously detected by routine callers and were not further analyzed. Among the remaining 65, 13 were considered likely true positives after visual inspection using IGV. Experimental validation was performed by Sanger/Nanopore long-read sequencing for these variants, all of which were confirmed. Eight were classified as (likely) pathogenic, including two frameshift duplications in MSH6, one splicing variant in BARD1, and five mobile element insertions in APC, BRCA2, and PALB2. Altogether, GRIDSS implementation increased diagnostic yield while maintaining feasibility for diagnostic workflows. Comprehensive workflow scheme for germline structural variant detection and results in our diagnostic setting.

Humans↗
PubMed2002

[PACS: from project to reality. Report of experiences on full digitalisation of the radiology department of a major hospital].

OBJECTIVE: To assess the time needed and the resulting effects of a complete digitalisation of a radiological department of a major hospital (856 beds, 28,000 in-patients, 35,000 out-patients/year) a pilot study was performed. This had to be done without interrupting routine services. RESULTS: After intensive preparations were performed and the hospital-network was completed, within a two year period all radiological functions (mammography excluded), reporting stations and archives were changed to a complete digital workflow. All modalities (provided by 3 different companies) are now connected by DICOM-work lists. The picture-files (4 GB/day) are automatically routed to the work-stations (n = 10), where the reporting and file shows are performed, to the digital archive and to the peripheral viewing-stations (n = 44). The distribution of the digital pictures takes place all over the hospital including the ORs and special units. We accomplished, to connect electronically the report and the image data. The clinical file shows are also performed completely digitally. The access to the data of the deep archive is possible by the dept. of radiology without any manual interaction. The film consumption was reduced to an amount of less than 10%, as compared to the prior PACS situation. Since PACS has been introduced the radiological productivity increased by more than 15% and throughput-time was clearly reduced. CONCLUSIONS: The complete digitalisation increases productivity and attractiveness of a hospital-radiology and helps to shorten diagnostic and therapeutic decision-making. The transfer from a conventional to a digital workflow is possible without interrupting the clinical services. Extensive preparations and ongoing assistance of such projects though are clearly needed.

Computer Systems↗
PubMed2026

Prospective clinical validation of targeted long-read sequencing for preimplantation genetic testing of α-thalassaemia.

BACKGROUND: Preimplantation genetic testing for monogenic disorders (PGT-M) can prevent transmission of severe α-thalassaemia, but conventional workflows remain limited by family-specific assay design for direct variant detection, dependence on additional family samples for haplotype construction, and labour-intensive multi-step procedures across several platforms. Targeted long-read sequencing-based PGT-M for α-thalassaemia (tlrPGT-α-thal) integrates direct variant detection and haplotype linkage analysis within a single assay, but prospective clinical validation is lacking. METHODS: This prospective clinical study enrolled 103 families at high risk of transmitting α-thalassaemia at a reproductive medicine centre between August 2024 and March 2025. All families underwent blinded parallel analysis using both conventional NGS-based PGT-M (comparator) and tlrPGT-α-thal. RESULTS: In the primary concordance analysis, tlrPGT-α-thal was fully concordant with conventional NGS-based PGT-M (507/507, 100.0%; exact 95% CI, 99.3-100.0). Direct variant detection was successful in 501/507 embryos (98.82%; 95% CI, 97.4-99.6), haplotype linkage was established in 505/507 embryos (99.61%; 95% CI, 98.6-100.0), and one meiotic recombination event was identified. Among 93 families proceeding to embryo transfer, 57 pregnancies underwent invasive prenatal diagnosis, and all were concordant with the corresponding tlrPGT-α-thal results. Of the 26 comparator-inconclusive embryos, tlrPGT-α-thal resolved 6 complex cases, including cases with incomplete pedigrees or insufficient informative SNPs. Among the remaining 20 embryos with HBA-region aneuploidies, genotype and parental origin could be determined in 12. CONCLUSIONS: The findings show that tlrPGT-α-thal enables direct detection of diverse α-thalassaemia-causing variants together with efficient haplotype linkage analysis within a single workflow, without requiring family-specific assay design or additional family samples. The method demonstrated high diagnostic accuracy while providing added value in complex scenarios. Taken together, tlrPGT-α-thal represents a simplified and broadly applicable strategy for α-thalassaemia PGT-M.

Humans↗
PubMed2026

Integrating Radiogenomics and CSF-Based Liquid Biopsy Sequencing for Precision Neuro-Oncology.

Glioblastoma and diffuse gliomas pose major therapeutic challenges due to marked intratumoral heterogeneity, limited tissue accessibility, and the blood-brain barrier. Tissue-based next-generation sequencing (NGS) remains essential for WHO CNS5 molecular classification, yet it is invasive and poorly suited to serial monitoring. Two complementary non- or minimally invasive approaches have advanced rapidly: radiogenomics, which correlates multiparametric MRI features with genomic alterations, and cerebrospinal fluid (CSF) liquid biopsy sequencing, which detects circulating tumor DNA with high tissue concordance. This review examines the independent progress and synergistic integration of radiogenomics and CSF-NGS. Imaging signatures can non-invasively predict key drivers (IDH1/2, EGFR, TERT, PTEN, TP53) and molecular subtypes, while CSF-ctDNA sequencing enables real-time assessment of clonal evolution, therapy resistance (including post-temozolomide hypermutation), and residual disease. We discuss technical considerations, performance metrics, multimodal artificial-intelligence fusion, and emerging clinical applications for diagnosis, prognosis, treatment selection, and longitudinal surveillance. Critical challenges, standardization, prospective validation, and workflow integration are highlighted. By combining the spatial phenotypic information of radiogenomics with the temporal genomic resolution of CSF sequencing, this multimodal strategy offers a promising path toward precision neuro-oncology and reduced reliance on repeated invasive sampling.

Humans↗
PubMed2004

Child Health Improvement through Computer Automation: the CHICA system.

Clinical guidelines are prevalent but frequently not used. Computer reminder systems can improve adherence to guidelines but have not been widely adopted. We present a computer-based decision support system that combines these elements: 1) pediatric preventive care guidelines encoded in Arden Syntax; 2) a dynamic, scannable paper user interface; and 3) a HL7-compliant interface to existing electronic medical record systems. The result is a system that both delivers "just in time" patient-relevant guidelines to physicians during the clinical encounter and accurately captures structured data from all who interact with the system. The system performs these tasks while remaining sensitive to the workflow constraints of a busy outpatient pediatric practice.

Algorithms↗
PubMed2026

Artificial intelligence in kidney cancer: a review of clinical applications across the disease spectrum.

PURPOSE OF REVIEW: This review examines recent advances (2024-2025) in the application of artificial intelligence (AI) to kidney cancer diagnosis, prognosis, and treatment planning. It categorizes studies across 13 clinical scenarios to assess where AI offers the most clinical utility. RECENT FINDINGS: AI models have demonstrated strong performance in a range of tasks including tumor grading, subtype classification, survival prediction, and risk stratification. Integration of radiomics, genomics, and histopathology has enabled personalized, noninvasive, and timely decision-making. The highest-performing models used CT-based radiomics, particularly for predicting progression-free and recurrence-free survival. However, performance varies across tasks and tumor subtypes, with lower accuracy in detecting oncocytomas or benign vs. malignant differentiation. AI applications in metastatic and nonresected cases remain underexplored, and ultrasound remains a largely under researched modality. While some models improve diagnostic accuracy and workflow efficiency, broader validation across diverse populations is still needed. SUMMARY: AI is transforming kidney cancer care across multiple clinical stages. Although promising, real-world implementation demands ongoing validation and postdeployment monitoring to prevent performance degradation due to distributional drift. AI's integration with multimodal data offers substantial potential to improve outcomes and reduce overtreatment.

Humans↗
PubMed2001

Impact of an electronic information system on physician workflow and data collection in the intensive care unit.

OBJECTIVE: To test the hypotheses that: (1) integrating information processing tasks using an electronic clinical information system (ECIS) decreases time to complete these tasks by hand; and (2) structured data entry encourages generation of more detailed records and capture of specific data elements even when entry is voluntary. DESIGN: Prospective observational time analysis during medical documentation tasks. Retrospective analysis of clinical documentation completed by hand or electronically. SETTING: Eleven bed pediatric intensive care unit within an academic medical center. PARTICIPANTS: Five pediatric intensive care medicine attending physicians. MEASUREMENTS: Compared handwritten and electronic documentation to determine: (1) time spent entering data or composing notes; (2) number of descriptors documenting patients' physical exams; (3) users' preferences for structured or unstructured data entry; (4) frequency of documenting specific data elements related to nutritional support. RESULTS: Documentation time varied by user but not charting method: it took 13 % less time to document using the ECIS but this was not significant. Electronic documents were more detailed than handwritten containing 50 % more descriptors (17.8 +/- 1.4 vs 11.6 +/- 1.4) overall and some data elements that were not handwritten: information related to nutritional supplementation was recorded in 13 % of electronic documents but in none of 89 handwritten documents. CONCLUSIONS: Electronic and handwritten documentation consumed equal amounts of time. Structured entry, compared to handwriting, may encourage recording of specific or otherwise unincorporated data elements resulting in a more detailed record. This suggests that user interfaces and decision support components may influence both the types and complexity of clinical data recorded by caregivers.

Analysis of Variance↗
PubMed2003

Guideline validation in multiple trauma care through business process modeling.

Clinical guidelines can improve the quality of care in multiple trauma. In our Department of Trauma Surgery a specific guideline is available paper-based as a set of flowcharts. This format is appropriate for the use by experienced physicians but insufficient for electronic support of learning, workflow and process optimization. A formal and logically consistent version represented with a standardized meta-model is necessary for automatic processing. In our project we transferred the paper-based into an electronic format and analyzed the structure with respect to formal errors. Several errors were detected in seven error categories. The errors were corrected to reach a formally and logically consistent process model. In a second step the clinical content of the guideline was revised interactively using a process-modeling tool. Our study reveals that guideline development should be assisted by process modeling tools, which check the content in comparison to a meta-model. The meta-model itself could support the domain experts in formulating their knowledge systematically. To assure sustainability of guideline development a representation independent of specific applications or specific provider is necessary. Then, clinical guidelines could be used for eLearning, process optimization and workflow management additionally.

Humans↗
PubMed2002

Guideline validation in multiple trauma care through business process modeling.

Clinical guidelines can improve the quality of care in multiple trauma. In our Department of Trauma Surgery a specific guideline is available paper-based as a set of flowcharts. This format is appropriate for the use by experienced physicians but insufficient for electronic support of learning, workflow and process optimization. A formal and logically consistent version represented with a standardized meta-model is necessary for automatic processing. In our project we transferred the paper-based into an electronic format and analyzed the structure with respect to formal errors. Several errors were detected in 7 error categories. The errors were corrected to reach a formal and logically consistent process model. In a second step the clinical content of the guideline was revised interactively using a process modeling tool. Our study reveals that guideline development should be assisted by process modeling tools, which check the content in comparison to a meta-model. The meta-model itself could support the domain experts in formulating their knowledge systematically. To assure sustainability of guideline development a representation independent of specific applications or specific provider is necessary. Then clinical guidelines could be used for training, process optimization and workflow management additionally.

Germany↗
PubMed2026

Evaluation of amplicon-based nanopore sequencing for foot-and-mouth disease viruses in clinical and environmental samples.

Foot-and-mouth disease (FMD) causes severe global economic loss, necessitating rapid viral characterization. Nanopore sequencing provides a simple, real-time workflow suitable for on-site outbreak response, addressing the limitations of conventional methods. In this study, we optimized a previously published amplicon-based protocol and used this method to characterize a diverse range of samples (vesicular fluid, epithelium, serum, nasal/oral swabs, and environmental samples) collected during FMD outbreaks in 2025 in the Republic of Korea. Of the 129 samples collected, we successfully recovered complete genomes from 37 samples and VP1 sequences from 85 samples. Amplifying the S-fragment in isolation and separately barcoding each pool of PCR amplicons markedly improved sequence recovery. Furthermore, sequencing success depended on viral load and sample type. Based on comparisons with real-time RT-PCR results, whole-genome sequence (WGS) recovery exceeded 77.3% at cycle threshold (Ct) values ≤25 across all clinical samples. In the Ct > 30 category, serum samples yielded the highest WGS recovery rates (44.4%). This rate was markedly higher than the success rates observed for epithelium (20.0%) and nasal swabs (9.1%), whereas oral swabs and environmental samples failed to yield any sequences (0%). However, VP1 recovery from environmental samples reached 80% at Ct ≤ 30 (8/10), providing an approach to enable non-invasive monitoring. These findings demonstrate that amplicon-based nanopore sequencing is a practical method for the rapid generation of genomic data during FMD outbreaks.IMPORTANCEAlthough rapid detection and genomic data analysis are crucial for effective foot-and-mouth disease (FMD) control, the collection of these data can be challenging for certain sample types and impacted by reduced viral loads that result from nationwide FMD vaccination. This study provides a practical solution through large-scale evaluation of an optimized amplicon-based nanopore sequencing protocol to enhance the sequencing success rates for both clinical and environmental samples. Using a modified protocol to enhance genome recovery, we demonstrated that sequence data could be retrieved from diverse sample types (even with high real-time RT-PCR cycle threshold values). We identified serum as the most suitable sample, with environmental sample sequencing allowing for non-invasive monitoring during outbreaks. These results support the use of nanopore sequencing for rapid genomic analysis, particularly in outbreak responses, such as rapid surveillance, emergency vaccine selection, and epidemiological monitoring.

Foot-and-Mouth Disease↗
PubMed2003

A framework for classifying decision support systems.

BACKGROUND: Computer-based clinical decision support systems (CDSSs) vary greatly in design and function. A taxonomy for classifying CDSS structure and function would help efforts to describe and understand the variety of CDSSs in the literature, and to explore predictors of CDSS effectiveness and generalizability. OBJECTIVE: To define and test a taxonomy for characterizing the contextual, technical, and workflow features of CDSSs. METHODS: We retrieved and analyzed 150 English language articles published between 1975 and 2002 that described computer systems designed to assist physicians and/or patients with clinical decision making. We identified aspects of CDSS structure or function and iterated our taxonomy until additional article reviews did not result in any new descriptors or taxonomic modifications. RESULTS: Our taxonomy comprises 95 descriptors along 24 descriptive axes. These axes are in 5 categories: Context, Knowledge and Data Source, Decision Support, Information Delivery, and Workflow. The axes had an average of 3.96 coded choices each. 75% of the descriptors had an inter-rater agreement kappa of greater than 0.6. CONCLUSIONS: We have defined and tested a comprehensive, multi-faceted taxonomy of CDSSs that shows promising reliability for classifying CDSSs reported in the literature.

Classification↗
PubMed2002

[Modern operations management in workflow operation. Spectrum of responsibilities and challenges for the future].

The operating unit is one of the cost-intensive facilities in a surgical clinic with a pacemaking function for most of the internal procedures. The power of performance of the operating unit is based on the co-operation of all disciplines and professions involved. The key to management of the operating unit is not only to co-ordinate the daily procedures, but also to interact with support personnel. To ensure successful OR management, the internal structure of the OR must fit the clinical tasks and the available quantity of personnel in each profession must be co-ordinated. Sufficient utilization of resources and equipment must be guaranteed without cost-intensive over-capacities and patient flow must be orientated to OR capacities. The development of such a business structure requires the management to clearly define the goal, to know the actual on-site data in detail with regard to the idiosyncratic workings of each speciality and to clearly assign the competence of each member of the team working in the OR. Co-ordination of the operating unit is the main task of OR management, which must ensure the following: transparent and co-ordinated schedule management in the various operative specialities, goal-directed changes of the schedule with incorporation of emergencies, as well as effective organization of staff. In order to realize these tasks, it is reasonable to implement interdisciplinary rules of procedures. In addition, the assignment of a neutral decision-making body within the OR and the creation of an information center for all OR personnel. The challenge of OR organization in the future is to implement more effective documentation systems and active controlling within the OR. One can ensure adequate utilization of resources in the OR with prospectively oriented planning. Better transparence of operations in the OR contributes to increased efficiency. Implementation of quality management is the foundation for a successfully operating surgical hospital. Not only the productivity of individual members of the staff, but also the precise documentation of the quality of results will become important parameters in a successful surgical hospital, whose nucleus is the OR.

Efficiency, Organizational↗