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PubMed2004

Adaptive guideline-based treatment workflows with AdaptFlow.

One goal in modern medicine is to increase the treatment quality. A major step towards this aim is to support the execution of standardized, guideline-based clinical protocols, which are used in many medical domains, e.g., for oncological chemotherapies. Standardized chemotherapy protocols contain detailed and structured therapy plans describing the single therapy steps (e.g., examinations or drug applications). Therefore, workflow management systems offer good support for these processes. However, the treatment of a particular patient often requires modifications due to unexpected infections, toxicities, or social factors. The modifications are described in the treatment protocol but not as part of the standard process. To be able to further execute the therapy workflows in case of exceptions running workflows have to be adapted dynamically. Furthermore, the physician should be supported by automated exception detection and decision support for derivation of necessary modifications. The AdaptFlow prototype offers the required support for the field of oncological chemotherapies by enhancing a workflow system with dynamic workflow adaptation and rule based decision support for exception detection and handling.

Clinical Protocols↗
PubMed1984

Hospital design to support greater operating efficiency.

With the new imperative on cost containment and particular emphasis on prospective payment, hospital design must support greater productivity. It is incumbent on architects and engineers to reduce construction costs; but more importantly, to design facilities that improve personnel productivity. Several approaches to designing for efficiency are discussed including improving the development process; systems building, ease of maintenance, and conserving energy; developing the model hospital; minimizing travel throughout the hospital; centralization vs. decentralization; automating support systems; designing for growth and change; analyzing workflow; utilizing swing space; and emphasizing consumer centered care.

Efficiency↗
PubMed1995

ASOP: a new method and tools for capturing a clinical encounter.

ASOP is a proposed method for future medical record notation. This permutation of the original POMR-SOAP method is necessary to provide the standardized workflow and medical nomenclature which will be essential for automated medical record systems and forms-based encounter recording. The development of an ASOP system is dependent on tools to map assessment to appropriate terminology within a universal medical dictionary and generate intelligent queries across the World-Wide-Web. In this study we intend to demonstrate the need for change in the POMR system and highlight some of the current tools in development to make the ASOP method the medical record notation system of choice.

Computer Communication Networks↗
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↗
PubMed1990

Automated differential white cell counts: a critical appraisal.

The differential leukocyte count represents a substantial proportion of the workload in routine haematology laboratories. The traditional procedure, in which a technologist scans a Romanowsky-stained blood film and classifies 100 cells, is both labour-intensive and imprecise. The imprecision of the visual DLC is primarily a function of the small number of cells counted. To achieve a significant improvement, however, it would be necessary to count an enormous number of cells, which would be extremely costly in terms of human time and effort. Automation is thus desirable for both economic and clinical reasons. Of the various technological approaches proposed, only two have been developed to the level of marketable devices: digital image processing, and flow cytochemistry. In digital image processing systems, Romanowsky-stained blood films were scanned by a computer-controlled microscope, and leukocytes identified on the basis of parameters analogous to those used by human observers. These systems were relatively slow, offering only a limited degree of automation, and therefore failed to provide significant improvements in terms of workflow and counting statistics. No such instruments are currently marketed. Flow-cytochemical analysers, which classify leukocytes primarily on the basis of size and myeloperoxidase activity, have been available commercially for 15 years, and their clinical utility is well established. A number of haematology analysers offer screening DLCs, providing neutrophil and lymphocyte counts in cases that do not have major abnormalities of the leukocyte population. The performance of these systems depends in large part on their operating environment. Three new automated DLC analysers employing flow cytometric technology have recently been announced, but these have not yet been formally evaluated.

Autoanalysis↗
PubMed1997

Hopper: software for automating data tracking and flow in DNA sequencing.

MOTIVATION: Genome-scale DNA sequencing is a multistep process in which large numbers of small template clones are propagated, purified, sequenced and analyzed on acrylamide gels. A significant challenge to these projects is the scale at which the data handling must be done. Hence, large-scale sequencing facilities will benefit from tracking template DNA information (purification methods, reaction and electrophoresis conditions) in a systematic fashion. A lack of software tools that support automated sample entry, and automatic data storage, retrieval and analysis are a major hindrance to recording and using laboratory workflow information to monitor the overall quality of data production. RESULTS: The UNIX file system has been used to prototype automation of the flow of data from the ABI sequencer to a data repository. Data are automatically processed by a central Perl program, Hopper, which runs a series of programs that analyze data quality (read length estimate, fraction of indeterminate bases, and number of contaminating and repetitive sequences), assemble shotgun sequence data, and generates simple reports describing the results.

Database Management Systems↗
PubMed2005

Utility of lab-on-a-chip technology for high-throughput nucleic acid and protein analysis.

On-chip electrophoresis can provide size separations of nucleic acids and proteins similar to more traditional slab gel electrophoresis. Lab-on-a-chip (LoaC) systems utilize on-chip electrophoresis in conjunction with sizing calibration, sensitive detection schemes, and sophisticated data analysis to achieve rapid analysis times (<120 s). This work describes the utility of LoaC systems to enable and augment systems biology investigations. RNA quality, as assessed by an RNA integrity number score, is compared to existing quality control (QC) measurements. High-throughput DNA analysis of multiplex PCR samples is used to stratify gene sets for disease discovery. Finally, the applicability of a high-throughput LoaC system for assessing protein purification is demonstrated. The improvements in workflow processes, speed of analysis, data accuracy and reproducibility, and automated data analysis are illustrated.

DNA↗
PubMed2006

Optimising workflow in andrology: a new electronic patient record and database.

AIM: To improve workflow and usability by introduction of a new electronic patient record (EPR) and database. METHODS: Establishment of an EPR based on open source technology (MySQL database and PHP scripting language) in a tertiary care andrology center at a university clinic. Workflow analysis, a benchmark comparing the two systems and a survey for usability and ergonomics were carried out. RESULTS: Workflow optimizations (electronic ordering of laboratory analysis, elimination of transcription steps and automated referral letters) and the decrease in time required for data entry per patient to 71%+/-27%, P<0.05, lead to a workload reduction. The benchmark showed a significant performance increase (highest with starting the respective system: 1.3+/-0.2 s vs. 11.1+/-0.2 s, mean+/-SD). In the survey, users rated the new system at least two ranks higher over its predecessor (P<0.01) in all sub-areas. CONCLUSION: With further improvements, today's EPR can evolve to substitute paper records, saving time (and possibly costs), supporting user satisfaction and expanding the basis for scientific evaluation when more data is electronically available. Newly introduced systems should be versatile, adaptable for users, and workflow-oriented to yield the highest benefit. If ready-made software is purchased, customization should be implemented during rollout.

Andrology↗
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↗
PubMed2002

Automated transport and sorting system in a large reference laboratory: part 1. Evaluation of needs and alternatives and development of a plan.

BACKGROUND: Our laboratory, a large, commercial, esoteric reference laboratory, sought some form of total laboratory automation to keep pace with rapid growth of specimen volumes as well as to meet competitive demands for cost reduction and improved turnaround time. METHODS: We conducted a systematic evaluation of our needs, which led to the development of a plan to implement an automated transport and sorting system. We systematically analyzed and studied our specimen containers, test submission requirements and temperatures, and the workflow and movement of people, specimens, and information throughout the laboratory. We performed an intricate timing study that identified bottlenecks in our manual handling processes. We also evaluated various automation options. RESULTS: The automation alternative viewed to best meet our needs was a transport and sorting system from MDS AutoLab. Our comprehensive plan also included a new standardized transport tube; a centralized automated core laboratory for higher volume tests; a new "automation-friendly" software system for order entry, tracking, and process control; a complete reengineering of our order-entry, handling, and tracking processes; and remodeling of our laboratory facility and specimen processing area. CONCLUSIONS: The scope of this project and its potential impact on overall laboratory operations and performance justified the extensive time we invested (nearly 4 years) in a systematic approach to the evaluation, design, and planning of this project.

Automation↗
PubMed2026

nf-core/pacsomatic: a scalable somatic analytic pipeline using PacBio HiFi data.

MOTIVATION: Pacific Biosciences (PacBio) HiFi long-read sequencing enables robust characterization of complex genomic regions, repetitive elements, and structural variants (SVs) that are often inaccessible to short-read technologies. To fully leverage HiFi reads to advance cancer genomics and epigenetics, researchers require an end-to-end, scalable and optimized bioinformatics workflow. The nf-core framework meets this need by providing rigorously tested, community-curated pipelines that ensure reproducibility, transparency, and broad compatibility across computational environments. RESULTS: We present nf-core/pacsomatic, an automated Nextflow DSL2 pipeline designed for comprehensive paired tumor-normal somatic analysis using PacBio HiFi data. The workflow includes steps for read alignments against reference genome, somatic SNV/indel, SV, and CNV calling, CpG methylation profiling and differential methylation region (DMR) detection. Additional downstream modules support functional annotation, mutational signature analysis, tumor purity and ploidy estimation, and homologous recombination deficiency (HRD) assessment. Utilizing nf-core's modular design and containerized execution, nf-core/pacsomatic provides a stable framework for the reproducible discovery of biological insights. AVAILABILITY: nf-core/pacsomatic is available under the MIT License at nf-core (https://nf-co.re/pacsomatic) and github (https://github.com/nf-core/pacsomatic).

Software↗
PubMed2026

Towards a Robust cell-free DNA Isolation Protocol for NGS Applications in a Clinical Molecular Diagnostics Setting.

Cell-free DNA (cfDNA), released from apoptotic and necrotic cells into body fluids, is a non-invasive source of genetic information for disease prediction, diagnosis, and monitoring. However, its low abundance makes cfDNA highly susceptible to various pre-analytical influences, potentially increasing high molecular weight (HMW) or genomic DNA (gDNA) compromising downstream cfDNA analyses. This study evaluated the impact of different cfDNA-stabilizing blood collection tubes (BCT; Cell-Free DNA BCT, Streck; S-Monovette cfDNA Exact, Sarstedt) stored at room temperature for 1, 5, or 10 days, prior to plasma isolation using different isolation methods (magnetic bead-based or silica column-based) on cfDNA stability and yield. DNA quantity and quality were assessed by fluorometric quantification, automated fragment analysis, and gene-specific quantitative PCR. Streck-based workflows maintained stable cfDNA yields and characteristic mononucleosomal fragmentation profiles across all storage times. In contrast, Sarstedt tubes showed reduced cfDNA concentrations after 5 days and a pronounced increase at 10 Days, accompanied by high-molecular weight DNA patterns consistent with white-blood cells (WBC) lysis. These trends were largely independent of the extraction method. Overall, the results demonstrate that blood collection tube chemistry critically influences cfDNA integrity during delayed processing. Streck tubes, particularly when combined with silica column-based isolation method, provided the most robust and reproducible workflow for routine molecular diagnostics, whereas Sarstedt tubes produced physiologically implausible results after extended storage.

blood collection tubes↗
PubMed2005

Automating the recognition and prioritization of needed preventive services: early results from the CHICA system.

An ever-growing plethora of preventive services guidelines threatens to overwhelm primary care providers who are expected to recognize and prioritize these needed services for each patient. The Child Health Improvement through Computer Automation (CHICA) system was designed to facilitate this process through a workflow-sensitive interface that gathers and distills the most relevant patient data within pediatric settings. We evaluated family responses to 21 CHICA questions that assess risk factors and health behaviors over a three month period. 3005 patients provided 15,434 responses to these questions, and 1756 or 11.3% of these suggest risk factors which merit attention. This preliminary analysis suggests that, using CHICA, families identify significant risk factors that our clinicians acknowledge are often overlooked given the realities of practicing within this setting.

Adolescent↗
PubMed2005

CHASE, a charge-assisted sequencing algorithm for automated homology-based protein identifications with matrix-assisted laser desorption/ionization time-of-flight post-source decay fragmentation data.

We describe CHASE, a novel algorithm for automated de novo sequencing based on the mass spectrometric (MS) fragmentation analysis of tryptic peptides. This algorithm is used for protein identification from sequence similarity criteria and consists of four steps: (1) derivatization of tryptic peptides at the N-terminus with a negatively charged reagent; (2) post-source decay (PSD) fragmentation analysis of peptides; (3) interpretation of the mass peaks with the CHASE algorithm and reconstruction of the amino acid sequence; (4) transfer of these data to software for protein identifications based on sequence homology (Basic Local Alignment Search Tool, BLAST). This procedure deduced the correct amino acid sequence of tryptic peptide samples and also was able to deduce the correct sequence from difficult mass patterns and identify the amino acid sequence. This allows complete automation of the process starting from MS fragmentation of complex peptide mixtures at low concentration (e.g. from silver-stained gel bands) to identification of the protein. We also show that if PSD data are collected in a single spectrum (instead of the segmented mode offered by conventional matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) instrumentation), the complete workflow from MS-PSD data acquisition to similarity-based identification can be completely automated. This strategy may be applied to proteomic studies for protein identification based on automated de novo sequencing instead of MS or tandem MS patterns. We describe the Charge Assisted Sequencing Engine (CHASE) algorithm, the working protocol, the performance of the algorithm on spectra from MALDI-TOFMS and the data comparison between a TOF and a TOF-TOF instrument.

Algorithms↗
PubMed2006

Laboratory Information Management Software for genotyping workflows: applications in high throughput crop genotyping.

BACKGROUND: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow. RESULTS: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. CONCLUSION: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/gt-bt/lims/lims.asp.

Algorithms↗
PubMed2026

CoMR: an integrative scoring pipeline for comprehensive mitochondrial proteome reconstruction across eukaryotes.

Mitochondrial proteome reconstruction from eukaryotic sequence data typically relies on prediction of mitochondrial targeting signals (MTSs). However, MTS predictors are primarily trained on model organisms and may perform poorly in phylogenetically divergent lineages or in organisms with atypical or reduced targeting sequences. Accurate reconstruction therefore requires integration of complementary sources of evidence beyond targeting prediction alone. We developed Comprehensive Mitochondrial Reconstructor (CoMR), an integrative workflow that combines targeting prediction, curated homology searches, large-scale similarity searches, and automated phylogenetic analysis within a unified scoring framework. Benchmarking on the model yeast Saccharomyces cerevisiae yielded strong discriminatory performance [receiver operating characteristic (ROC)-area under the curve (AUC)&#x2009;=&#x2009;0.92], exceeding standalone prediction with TargetP2, a predictor of N-terminal targeting peptides (ROC-AUC&#x2009;=&#x2009;0.72). In the divergent anaerobic protist Paratrimastix pyriformis, CoMR maintained robust performance (ROC-AUC&#x2009;=&#x2009;0.86) validated with an experimental proteome despite extreme class imbalance, achieving a precision-recall AUC of 0.183 (~78-fold enrichment over random expectation and&#x2009;~10-fold improvement over TargetP2). Ablation analyses demonstrate that predictive performance is robust to individual evidence-layer removal, while overlap analyses showed that homology-based searches recovered candidates missed by targeting predictors, particularly in P. pyriformis. Overall, CoMR improves mitochondrial proteome reconstruction over targeting prediction alone and provides a reproducible workflow for predicting mitochondrial and mitochondrion-related organelle protein repertoires across eukaryotes to aid investigations of organelle evolution and proteome reduction.

Proteome↗
PubMed2026

LCR-modules: a collection of workflows for cancer genome analysis.

MOTIVATION: The surge of genomic data from advanced sequencing technologies is outpacing current analytical pipelines. We introduce LCR-modules, an open-source suite of bioinformatics tools designed for flexible and automated cancer genome data analysis. LCR-modules enables reproducible analysis of diverse cancer genomics data at scale. The suite comprises 49 Snakemake-based workflows organized into three levels, facilitating tasks from low-level quality control to complex cohort-level analyses. LCR-modules supports various sequencing types and integrates pipelines such as mutation calling, expression quantification, and cohort-level aggregation, ensuring flexibility and reproducibility. LCR-modules represents a significant advancement in genomic data analysis, reducing barriers in reproducibility and scalability and has already been applied to a combination of exomes and genomes from over 10&#x2009;800 samples. AVAILABILITY: No new data were generated in support of this research. The source code for the LCR-modules is openly available at https://github.com/LCR-BCCRC/lcr-modules.

Software↗