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At least 163 records · Page 9Linked to original sources
PubMed2025

DNA methylation and machine learning: challenges and perspective toward enhanced clinical diagnostics.

DNA methylation is an epigenetic modification that regulates gene expression by adding methyl groups to DNA, affecting cellular function and disease development. Machine learning, a subset of artificial intelligence, analyzes large datasets to identify patterns and make predictions. Over the past two decades, advances in bioinformatics technologies for arrays and sequencing have generated vast amounts of data, leading to the widespread adoption of machine learning methods for analyzing complex biological information for medical problems. This review explores recent advancements in DNA methylation studies that leverage emerging machine learning techniques for more precise, comprehensive, and rapid patient diagnostics based on DNA methylation markers. We present a general workflow for researchers, from clinical research questions to result interpretation and monitoring. Additionally, we showcase successful examples in diagnosing cancer, neurodevelopmental disorders, and multifactorial diseases. Some of these studies have led to the development of diagnostic platforms that have entered the global healthcare market, highlighting the promising future of this field.

Humans↗
PubMedDate not supplied

Genomic messaging system and DNA mark-up language for information-based personalized medicine with clinical and proteome research applications.

The convergence of clinical medicine and the Life Sciences, commencing with opportunities in clinical trials and clinically linked medical research, presents many novel challenges. The Genomic Messaging System (GMS) described here was originally developed as a tool for assembling clinical genomic records of individual and collective patients, and was then generalized to become a flexible workflow component that will link clinical records to a variety of computational biology research tools, for research and ultimately for a more personalized, focused, and preventative healthcare system. Prominent among the applications linked are protein science applications, including the rapid automated modeling of patient proteins with their individual structural polymorphisms. In an initial study, GMS formed the basis of a fully automated system for modeling patient proteins with structural polymorphisms as a basis for drug selection and ultimately design on an individual patient basis.

Clinical Medicine↗
PubMed2005

Workflow and problem domain as information planning tools in a pediatric clinic--defining present and future information technology needs.

In 2002, $22.4 billion were spent on hospital construction in the US. With lifetimes for new buildings expected to be decades, planning a building's information technology infrastructure must take into account present and future needs. Workflow measurement and the definition of problem domain have been advanced as essential tools in addressing current requirements while anticipating future needs. To examine these, stakeholders must be identified-including both those who will use the facility and those who will be involved in the IT planning and long term support.

Child↗
PubMed2005

OrthoPilot total hip arthroplasty workflow and surgery.

To analyze the workflow and navigation principles of the OrthoPilot total hip arthroplasty (THA) Version 2.0 (B. Braun-Aesculap, Tuttlingen, Germany), a consecutive series of 60 patients was used to compare the navigated intraoperative data and postoperative measurements of stem and cup position. Within the safe zone, 96.3% of 54 acetabular cups were positioned. The rotational accuracy of femoral instruments was 65 degrees in 41 THAs. The femoral offset was medialized by 6.05 mm in 76% and lateralized by 2.1 mm in 14%. The data for leg length and range of motion from 60 THAs and the navigated data were similar. Thus, the first clinical validation of the workflow of the OrthoPilot THA Version 2.0 is encouraging.

Arthroplasty, Replacement, Hip↗
PubMed2026

Cytokines and Inflammatory Gene Polymorphisms Associated With Nosocomial Pulmonary Infection After Spontaneous Intracerebral Hemorrhage.

Nosocomial pulmonary infection is a frequent complication after spontaneous intracerebral hemorrhage and may worsen neurological recovery, prolong hospitalization, and increase clinical burden. This retrospective clinical-laboratory study presents a reproducible workflow for evaluating inflammatory biomarker and host immune-genetic profiles associated with nosocomial pulmonary infection after primary spontaneous intracerebral hemorrhage. Patients are classified according to whether nosocomial pulmonary infection occurs after admission. Peripheral venous blood is collected in the early post-admission period under standardized pre-analytical conditions. Serum is separated, aliquoted, and stored for enzyme-linked immunosorbent assay measurement of IL-1β, IL-6, IL-10, IL-17, IFN-γ, TNF-α, TLR2, TLR4, and TLR9. In parallel, genomic DNA is extracted from anticoagulated whole blood and used for polymerase chain reaction-restriction fragment length polymorphism genotyping of selected cytokine- and Toll-like receptor-related loci. The workflow also includes quality-control procedures for sample handling, duplicate ELISA measurements, DNA purity assessment, genotype calling, and repeat genotyping. Statistical analysis includes between-group comparison of clinical characteristics and biomarker levels, Hardy-Weinberg equilibrium testing, logistic regression analysis for genotype and allele associations, adjustment for relevant clinical covariates, and false-discovery-rate correction for multiple genetic comparisons. This combined clinical, inflammatory, and immune-genetic workflow may help characterize infection-risk profiles after spontaneous intracerebral hemorrhage, although prospective multicenter validation is still required before routine clinical application.

Humans↗
PubMed1999

Sophisticated hospital information system/radiology information system/picture archiving and communications system (PACS) integration in a large-scale traumatology PACS.

Picture archiving and communications system (PACS) in the context of an outpatient trauma care center asks for a high level of interaction between information systems to guarantee rapid image acquisition and distribution to the surgeon. During installation of the Innsbruck PACS, special aspects of traumatology had to be realized, such as imaging of unconscious patients without identification, and transferred to the electronic environment. Even with up-to-date PACS hardware and software, special solutions had to be developed in-house to tailor the PACS/hospital information system (HIS)/radiology information system (RIS) interface to the needs of radiologic and clinical users. An ongoing workflow evaluation is needed to realize the needs of radiologists and clinicians. These needs have to be realized within a commercially available PACS, whereby full integration of information systems may sometimes only be achieved by special in-house solutions.

Ambulatory Care Facilities↗
PubMed2006

Comparison of workflow and accuracy of identification and antimicrobial susceptibility testing of clinical isolates of Enterobacteriaceae, Pseudomonas aeruginosa and enterococci by Vitek 2 and routine methods.

Three hundred and fifty-three consecutive urine cultures growing Enterobacteriaceae, Pseudomonas aeruginosa or enterococci were subjected to parallel identification (ID) and antimicrobial susceptibility testing (AST) by Vitek 2 and routine methods, including simple screening tests or API 20 E for ID and standardized disc diffusion for AST. Accuracy of results, technician hands-on time required by both methods and time to results were compared. Vitek 2 correctly identified 322 (94.7%) of the 340 gram-negative isolates and 17 (81%) of the 21 Enterococcus faecalis strains. AST by Vitek 2 and disc diffusion gave category agreement for 4,058 (95.5%) of 4,248 organism-antimicrobial agent combinations. With MIC determination by E-test as reference, AST by Vitek 2 and disc diffusion produced 15 and 3 very major errors, respectively. Six (40%) of the fifteen very major errors by Vitek 2 were associated with trimethoprim-sulfamethoxazole. With an average of 22 specimens processed per day, use of Vitek 2 saved 80 min per day of technician hands-on time as compared to routine methods. Regarding the cost of hands-on worktime and consumables, use of Vitek 2 for identification of Escherichia coli-screened Enterobacteriaceae saved 0.70 p per sample in comparison to API 20 E. More than 80% of Enterobacteriaceae introduced to Vitek 2 in the morning could be reported by 16:00.

Anti-Bacterial Agents↗
PubMed2026

Clinical accuracy and short-term outcomes of intraoral photogrammetry for complete-arch implant rehabilitation: A retrospective multicentre study on 35 patients.

OBJECTIVES: To evaluate the clinical accuracy and short-term outcomes of complete-arch implant-supported fixed dental prostheses (ISFDPs) fabricated using an intraoral photogrammetry (IPG) based digital workflow in completely edentulous patients. METHODS: This multicenter retrospective clinical study included 35 patients rehabilitated with 52 complete-arch ISFDPs (10 FP1, 18 FP2 and 24 FP3 restorations) supported by 221 implants. All definitive prostheses were designed and fabricated using a fully digital workflow initiated by IPG acquisition with the Aoralscan Elite IPG® (SHINING 3D). The primary outcome was clinical accuracy, assessed at definitive prosthesis delivery through evaluation of passive fit using the Sheffield test and radiographic verification. Secondary outcomes included biologic and prosthetic complications, as well as implant and prosthesis survival rates during the follow-up. RESULTS: Passive fit was achieved in all definitive restorations (100%). Radiographic evaluation confirmed accurate marginal adaptation at the implant-prosthesis interface in all cases. No statistically significant differences in clinical accuracy were observed according to treated arch, number of supporting implants, or prosthetic design (P > .05). During a mean follow-up period of 12.1 ± 3.5 months, biologic and prosthetic complications were limited and generally minor. Implant survival was 99.5%, and prosthesis survival was 100%. CONCLUSIONS: Within the limitations of this retrospective clinical study, the IPG based workflow demonstrated high clinical accuracy and predictable short-term outcomes for complete-arch implant rehabilitation, consistently enabling passive fit and favorable prosthetic performance. CLINICAL RELEVANCE: IPG may represent a clinically reliable and predictable approach for complete-arch digital implant impression acquisition. The high rates of passive fit, together with the low incidence of biologic and prosthetic complications observed in this multicenter clinical study, support the use of IPG based workflows for the fabrication of complete-arch ISFDPs.

Humans↗
PubMed2026

An AI-assisted Clinical Decision Support System for Green Classification of Cystocele on Dynamic Transperineal Ultrasound.

Green classification of cystocele on dynamic transperineal ultrasound (TPUS) remains operator-dependent because it requires manual frame selection and landmark-based assessment of the Valsalva maneuver. We developed a workflow-oriented AI-assisted clinical decision support system for automated urethrovesical junction localization and dynamic Green classification and prospectively evaluated its standalone and reader-support performance. This diagnostic accuracy and reader study included 881 patients from a tertiary referral hospital, comprising a retrospective development cohort (n = 688) and an independent prospective test cohort (n = 193). A nested subset of 67 prospective patients was used for a reader study involving two junior and two intermediate radiologists under unaided and AI-assisted conditions. In the complete prospective test cohort, Green-AttGRU achieved a macro-averaged AUC of 0.939 (95% CI, 0.897-0.971) and an overall accuracy of 0.902 (95% CI, 0.860-0.943). In the reader study, overall accuracy increased from 0.761 to 0.821 without AI to 0.851-0.881 with AI, while macro-F1 increased from 0.660 to 0.777 to 0.820-0.860. Overall inter-reader agreement increased from a Fleiss' κ of 0.453 to 0.786, and pooled median interpretation time decreased from 26.7 s to 9.9 s. These findings support the preliminary feasibility of the system as a workflow-oriented decision-support tool for dynamic TPUS interpretation.

Humans↗
PubMed2026

Invasive mucinous adenocarcinoma of the lung: integrating molecular landscape, imaging phenotypes, and translational therapeutic strategies.

Invasive mucinous adenocarcinoma (IMA) of the lung is an uncommon but clinically important subtype of lung adenocarcinoma with distinctive radiologic, histopathologic, and molecular features. Its indolent symptoms, mucin-rich growth pattern, and frequent pneumonia-like or multifocal presentation can obscure early diagnosis and complicate distinction from infection, synchronous primary tumors, and intrapulmonary spread. This review integrates current evidence on the clinical course, imaging phenotypes, diagnostic workflow, histopathologic features, molecular alterations, tumor immune microenvironment, and treatment response patterns of IMA. Emphasis is placed on the relationship between radiologic appearance and underlying mucinous pathology, the clinical significance of spread through air spaces (STAS), and the need for adequate tissue sampling and comprehensive molecular profiling. Compared with non-mucinous lung adenocarcinoma, IMA is enriched for KRAS mutations and selected fusion or receptor alterations, whereas canonical EGFR mutations are less frequent. These biological differences help explain why treatment strategies extrapolated from broader non-small cell lung cancer (NSCLC) populations may be insufficient, particularly for multifocal, pneumonic-type, or advanced disease. Although surgery can provide favorable outcomes in localized disease, systemic therapy remains challenging, and the role of immunotherapy requires further clarification. Future progress will depend on integrated imaging-pathology-genomic models, prospective IMA-specific cohorts, and translational studies aimed at refining classification and developing individualized therapeutic strategies.

Invasive mucinous adenocarcinoma (IMA)↗
PubMed2006

A method for specification of structured clinical content in electronic health records.

The Copenhagen County is using clinical guidelines in the electronic health record development to provide documentation support, process support and decision support for the healthcare professionals. The electronic health record development is based on three main components: The first component is a national information model. The second component is a common classification system (SNOMED). The third key component is the so-called "clinical content". This paper describes the structured "clinical content", how it is linked to the clinical process, and how it is used to create clinical guidelines in the form of standard care plans. The Copenhagen County and MEDIQ has developed a methodology for identifying and specifying structured "clinical content" to be used in electronic health records. The method combines analyses of national clinical guidelines with local experience and practices and it heavily involves healthcare professionals. The method includes four main steps: Analyses of background material, analyses of clinical process-flow, mapping to standards (the national information model and the common classification system), and specification of the structured clinical content itself. Three secondary steps may be added to specify the clinical content in more detail: Workflow analyses, analyses of quality indicators, and decision analyses. This paper reports the experiences using the method and stresses the demand for a common exchange format and IT-tools for documenting clinical content in a formalised way.

Decision Support Systems, Clinical↗
PubMed1998

Strategies for problem list implementation in a complex clinical enterprise.

Although the Institute of Medicine states that a patient problem list should have a prominent place in the computer-based patient record, the design and function of the problem list is not a matter of universal agreement. Developer experience with implementation has been inconsistent, in part because of confusion on data standards, uncertain user acceptance of data entry, and minimal rewards for the clinician. I propose that necessary features of the problem list include: 1) clinical focus, 2) codification of problems, 3) support for problem resolution, 4) historicity of problems, 5) support for multiple clinical views, 6) integration of maintenance functions with workflow, 7) support for administrative reporting, and 8) integration with useful clinical tools. I describe the strategies that we employed to meet these goals while implementing the problem list in a computerized patient record serving a large, complex clinical enterprise. I further report the successful achievement of those goals based upon audits six months after implementation.

Diagnosis-Related Groups↗
PubMed1998

Continuing quality improvement procedures for a clinical PACS.

The University of California at San Francisco (USCF) Department of Radiology currently has a clinically operational picture archiving and communication system (PACS) that is thirty-five percent filmless, with the goal of becoming seventy-five percent filmless within the year. The design and implementation of the clinical PACS has been a collaborative effort between an academic research laboratory and a commercial vendor partner. Images are digitally acquired from three computed radiography (CR) scanners, five computed tomography (CT) scanners, five magnetic resonance (MR) imagers, three digital fluoroscopic rooms, an ultrasound mini-PACS and a nuclear medicine mini-PACS. The DICOM (Digital Imaging and Communications in Medicine) standard communications protocol and image format is adhered to throughout the PACS. Images are archived in hierarchical staged fashion, on a RAID (redundant array of inexpensive disks) and on magneto-optical disk jukeboxes. The clinical PACS uses an object-oriented Oracle SQL (systems query language) database, and interfaces to the Radiology Information System using the HL7 (Health Languages 7) standard. Components are networked using a combination of switched and fast ethernet, and ATM (asynchronous transfer mode), all over fiber optics. The wide area network links six UCSF sites in San Francisco. A combination of high and medium resolution dual-monitor display stations have been placed throughout the Department of Radiology, the Emergency Department (ED) and Intensive Care Units (ICU). A continuing quality improvement (CQI) committee has been formed to facilitate the PACS installation and training, workflow modifications, quality assurance and clinical acceptance. This committee includes radiologists at all levels (resident, fellow, attending), radiology technologists, film library personnel, ED and ICU clinician end-users, and PACS team members. The CQI committee has proved vital in the creation of new management procedures, providing a means for user feedback and education, and contributing to the overall acceptance of, and user satisfaction with the system. Well developed CQI procedures have been essential to the successful clinical operation of the PACS as UCSF Radiology moves toward a filmless department.

Computer Communication Networks↗
PubMed2003

Workflow-enabled distributed component-based information architecture for digital medical imaging enterprises.

Few information systems today offer a flexible means to define and manage the automated part of radiology processes, which provide clinical imaging services for the entire healthcare organization. Even fewer of them provide a coherent architecture that can easily cope with heterogeneity and inevitable local adaptation of applications and can integrate clinical and administrative information to aid better clinical, operational, and business decisions. We describe an innovative enterprise architecture of image information management systems to fill the needs. Such a system is based on the interplay of production workflow management, distributed object computing, Java and Web techniques, and in-depth domain knowledge in radiology operations. Our design adapts the approach of "4+1" architectural view. In this new architecture, PACS and RIS become one while the user interaction can be automated by customized workflow process. Clinical service applications are implemented as active components. They can be reasonably substituted by applications of local adaptations and can be multiplied for fault tolerance and load balancing. Furthermore, the workflow-enabled digital radiology system would provide powerful query and statistical functions for managing resources and improving productivity. This paper will potentially lead to a new direction of image information management. We illustrate the innovative design with examples taken from an implemented system.

Computer Communication Networks↗
PubMed2000

New aspects of image distribution and workflow in radiology.

The progressive use of digital image-generating devices and digital communication technology in clinical and practice environments implies changes in radiological workflow and asks for adequate quality assurance in the whole process of radiology report preparation. This improvement potential has to be rigorously reinvestigated with regard to up-to-date procedures and the full exploitation of supporting technologies like linguistic analysis, help desk and trouble ticket systems, competitive allocation algorithms, time-and-event monitoring, and intelligent agents. These approaches are to be evaluated in combination with business process analysis and shall help to reduce turnaround times for radiology reports while maintaining or even increasing quality-assurance levels.

Germany↗
PubMed2000

Radiology workflow and patient volume: effect of picture archiving and communication systems on technologists and radiologists.

This study was performed to evaluate the changes in workflow and efficiency in various clinical settings in the radiology department after the introduction of a picture archiving and communication system (PACS). Time and motion data were collected when conventional image management was used, and again after the introduction of a PACS. Changes in the elapsed time from examination request until the image dispatch to the radiologist, and from dispatch until report dictation, were evaluated. The relationship between patient volume and throughput was evaluated. The time from examination request until dispatch was significantly longer after the introduction of PACS for examinations taken on patients from the emergency department (ED) (pre-PACS, 20 minutes; post-PACS, 25 minutes; P < .0001), and for examinations taken on patients in the medical intensive care unit (MICU) (pre-PACS, 34 minutes; post-PACS, 42 minutes; P < .0001). The interval from image dispatch until report dictation shortened significantly after the introduction of PACS in the ED (pre-PACS, 38 minutes; post-PACS, 23 minutes; P < .0001) and in the outpatient department (OPD) (pre-PACS, 38 minutes; post-PACS, 20 minutes; P < .0001). Simple least squares regression showed a significant relationship between daily patient volume and the daily median time until report dictation (F = 43.42, P < .001). PACS slowed technologists by prolonging the quality-control procedure. Radiologist workflow was shortened or not affected. Efficiency is dependent on patient volume, and workflow improvements are due to a shift from batch to on-line reading that is enabled by the ability of PACS to route enough examinations to keep radiologists fully occupied.

Appointments and Schedules↗
PubMed2026

The Computational Revolution in Natural Product Research: A Data-Driven Roadmap for Next-Generation Drug Development.

Natural products (NPs) have historically provided the foundational scaffolds for drug development, yet traditional bioprospecting faces critical limitations: high rediscovery rates, laborious isolation workflows, and substantial attrition during clinical translation. The emergence of big data technologies is fundamentally transforming this landscape, enabling a shift from serendipity-based discovery toward systematic, data-driven approaches. This review examines how the integration of artificial intelligence (AI), machine learning (ML), and multi-omics datasets is accelerating natural product research across three key domains: (1) genome mining for biosynthetic gene cluster identification using platforms such as antiSMASH, (2) cheminformatics-driven prediction of structure-activity relationships and ADMET properties, and (3) metabolomics-guided dereplication to prioritize novel bioactive scaffolds. We evaluate the convergence of genomics, metabolomics, and computational chemistry in enabling in silico lead optimization and the discovery of cryptic metabolites from previously inaccessible microbial taxa. While challenges in data standardization and scalability persist, the synergy between big data and NP research is accelerating clinical translation. Despite persistent challenges in data standardization, scalability, and equitable benefit-sharing, the convergence of big data and NP research is poised to redefine drug development. These advances position computational NP research as a cornerstone of next-generation drug development.

big data analytics↗