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At least 19 records

Process mining for healthcare: Characteristics and challenges

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

59 BASIC BIOLOGICAL SCIENCES↗

Feature Engineering and Process Mining to Enable Hazard Detection in Health Information Technology

Motivation for this work originates from a recognized need for developing data-driven approaches through analysis of complex electronic health records. Specifically, we aim to enhance the reliability of health information technology (HIT) systems by detection of plausible HIT hazards in clinical order transactions. In the absence of well-defined event logs in corporate data warehouses, our proposed approach identifies relevant timestamped data fields that could indicate transactions in the clinical order life cycle generating raw event sequences. Subsequently, we adopt state transitions of the OASIS Human Task standard to map the raw event sequences and simplify the complex process that clinical radiology orders go through. We describe how the current approach provides the potential to investigate areas of improvement and potential hazards in HIT systems. The discussion concludes with a use case and opportunities for future applications.

Ozmen, Ozgur↗

Membrane-based solvent extraction for the recovery of rare earths from phosphate mining process streams

This study reports on the capture of rare earth elements (REEs) from phosphate industry process streams, including phosphoric acid (PA) sludge and phosphogypsum (PG), using a membrane solvent extraction (MSX) process. While MSX has been proven effective for a relatively concentrated feed, its effectiveness for dilute REEs solutions remains unexplored. Investigated PA-sludge and PG particles contain total REEs concentrations of ∼1100 and ∼320 ppm, respectively. Acid leaching, implemented to dissolve the REEs, significantly dilutes the REEs concentration to ∼210 ppm for PA-sludge leachate and ∼60 ppm for PG leachate. These low concentrations, compounded by the higher levels of non-REE ions and radioactive species, uranium (U) and thorium (Th), poses challenges to the MSX process. Here, we demonstrated that N,N,N′,N′-tetraoctyl-diglycolamide (TODGA) selectively binds REEs from a >3 M nitric-acid leachate while effectively rejecting U and Th. Concentrations of light REEs in strip solution were doubled compared to the feed, while heavy REEs were preferentially extracted. Furthermore, >99% purity gypsum, free of U and Th, was precipitated during the acid leaching process, aiding separation by removing significant amounts of non-REEs species (e.g., calcium) prior to the MSX process. Molecular simulations support the experimental data, suggesting preferential separation of heavy over light REEs. Based on these results, a cost-effective integrated process including pretreatment, acid leaching, MSX, and wastewater treatment is proposed for the co-recovery of REEs, phosphoric acid, gypsum, and U. This study shows MSX as a technically and economically feasible process for the recovery of REEs from low-concentration process streams, offering advantages over conventional solvent extraction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dual-use technologies for the mining, processing, and energy industries

Over the years, NASA has utilized several approaches towards transferring space technologies into the private sectors. Some of these approaches have been successful, others have had mixed results. The conventional approach usually involves identifying advanced NASA technologies and then searching for applications. Some approaches involve joint sponsorship, but mostly focus on technologies for space. The greatest success has occurred when market forces are used to determine technology initiatives. This paper describes an unconventional approach that was structured to drive out customer requirements for advanced technologies where NASA is also a customer on par with others. The approach used herein is best described as entrepreneurial deal-making. This approach is new and is working very well so far, but it is still too early, and the process is too immature, for quantitative evaluation of success. However, it is appropriate to share these experiences at this time in order to obtain feedback and improve our chances for success. In the needs identification stage, NASA is one of many users (customers), and in the subsequent development stage, NASA is one of many suppliers along with industry, academia, and other government organizations. This specific characteristic of the approach was a primary goal that was incorporated from inception. It was the viewpoint of the instigators (the authors) that if the activity was customer focused, it would: (1) have a higher probability for success since it will be driven by those who will reap the benefits; (2) be able to advocate and promote action if necessary, since it would be founded outside the federal government; (3) not be self-perpetuating; that is, if no common need could be found that had a reasonable return on investment, it would self-destruct; and (4) have increased stability from a broader base of support and not be dependent on NASA being the principal funding source. To date, the workshop activities have identified a collection of potential customers in NASA, other federal government, private industry, and academia who have common needs for advanced technologies.

Roberts, Barney B.↗

Lunar Mining and Processing: Considerations for Responsible Space Mining & Connections to Terrestrial Mining

The National Aeronautics and Space Administration (NASA) of the United States of America (US) has initiated the Artemis Moon to Mars program to send astronauts (the first woman and person of color) back to the lunar surface, create a sustainable human lunar exploration program, and lead the first human exploration mission to the Mars surface in the late 2030’s [1]. Besides reinvigorating human exploration beyond low Earth orbit not seen since the Apollo program and enabling new scientific activities and discoveries, a major objective of this program is to characterize the resources that exist on the Moon and Mars, and learn how to utilize them for human exploration and the commercialization of cis-lunar space. Commonly known as In Situ Resource Utilization (ISRU), the search for, acquisition, and processing of resources in space has the potential to greatly reduce the dependency on transporting mission consumables and infrastructure from Earth, thereby reducing mission costs, risks, and dependency on Earth. With the launch of Artemis I in November 2022 and the anticipation of several robotic missions to the Moon under the Commercial Lunar Payload Services (CLPS) program, greater recognition and excitement about NASA’s Artemis program and lunar exploration activities is growing in the public. With the recognition that past statements and concept videos of human exploration of the Moon are actually becoming real, there is also a growing awareness of the possible positive and negative consequences and impacts these exploration activities may have on the Moon and Mars. On the positive side, the development of ISRU and lunar mining and processing can enable and grow lunar surface exploration and cis-lunar commercial activities, as well as provide benefits to terrestrial industries through spin-in and spin-back of advanced technologies and autonomous operations. On the negative side, there is a perception that space mining will impact the lunar surface and environment negatively for science, and that cultural beliefs about the Moon need to be addressed and considered before these operations occur. This paper will begin to explore the potential driving attributes and guidelines that will address how best to maximize the lessons and connections to terrestrial mining to reduce the risk and cost of lunar ISRU and space commercial activities, enhance efforts to achieve the terrestrial ‘mine of the future’, and provide viable markets for space-derived technologies until commercial space mining is established. This paper will also begin to explore the potential driving attributes and guidelines that could address how to minimize the environmental and surface impacts of lunar ISRU and foster ‘responsible’ space mining that can be implemented until more official agreements and treaties are signed. The existing robust mining regulations adopted globally will be used as a basis for this examination and suggestions will be presented to adopt these agreements for use in space mining.

ISRU↗

Policy Reforms to Unleash Domestic Critical Minerals Mining and Processing

The United States faces growing strategic and economic risks due to its limited ability to mine, process, and refine the minerals required for national defense, energy systems, advanced manufacturing, and emerging technologies. Although the country possesses significant geological resources, development has been slowed by long and unpredictable permitting timelines, fragmented regulatory responsibilities, limited midstream processing capacity, and a shrinking technical workforce. These structural barriers have created supply chain vulnerabilities that constrain industrial growth and reduce national resilience. This report presents a comprehensive set of reforms intended to modernize the nation’s approach to critical minerals. The recommendations address federal permitting, environmental review processes, the legal framework governing mining activities, interagency coordination, domestic processing and refining capacity, and the education and workforce systems needed to support long term industry development. The analysis emphasizes practical steps to shorten project timelines, improve regulatory clarity, expand processing infrastructure, enable recovery from both conventional and nontraditional sources, and update outdated requirements that hinder the development of essential materials. Taken together, the recommended reforms would strengthen domestic supply chains, improve investment certainty, and reduce dependence on external minerals and processing infrastructure. By aligning policy, regulatory frameworks, and workforce capabilities with national needs, the United States can build a more resilient and secure critical minerals ecosystem that supports long term economic competitiveness and technological leadership.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Comparative Assessment of Data-driven Process Models in Health Information Technology

Process mining for conformance analysis consists of comparing a reference process model against a data-driven process model generated via log files from information technology systems. However, in the absence of a complete reference process model, we found no suggested approaches in the literature to address the need for evaluating process conformance among different healthcare facilities to assess standardization of care. Our goal is to find similarities and dissimilarities in data-driven process models among US Veterans Health Administration (VHA) facilities that can be indicative of patient safety issues. Our hypothesis was that the analysis would not produce statistically significant differences in outcome. We present a unique implementation of conformance analysis in process mining that consists of combining process mining, process mapping and statistical metrics. We illustrate our approach by applying it to the analysis of two clinical radiology order process models generated from healthcare data provided by two similar facilities in the VHA. The comparative assessment showed that about 70% of the orders completed successfully and 30% were not completed due to policy and duplications. Our analysis found a good statistical correlation between both facilities, as the Spearman’s correlation coefficient between facilities for the frequency of cases per total hours was 0.87879, for the frequency of cases by state transition was 0.79702 and for the throughput time per state transition was 0.63582. Additional statistical analyses using the Mann-Whitney U test and the root mean square error both produced values that were not significant. The foregoing approach validated our hypothesis by demonstrating a good statistical correlation of data describing the flow of clinical radiology orders absent a credible reference model. Finding good agreement between both facilities was important in confirming that the clinical orders flow in a similar manner, suggesting standardization of care.

97 MATHEMATICS AND COMPUTING↗

Some opportunities in teleoperated mining

Processes involved in remote control mining (fragmentation, material handling, ground and environmental control) are discussed with reference to longwall shear mining, the method which affords the greatest potential for the use of teleoperated systems. The breakup and haulage procedures are outlined, with attention to environmental control subsystems, i.e., noise and dust abatement. A description of a four-legged chock, attached to a section of a face conveyor and operated remotely, is presented.

Palowitch, E. R.↗

Towards a Comparative Assessment of Data-Driven Process Models in Health Information Technology

Process mining for conformance analysis focuses on comparing a reference process model against a data-driven process model that is generated via log files from information technology systems. While this approach is helpful when there is an existing process model in an organization, it leaves the question of what to do in the absence of a complete reference process model unanswered. In this paper, we present a comparative assessment approach that combines process mining, process mapping for dimensionality reduction, and statistical analysis. Our goal is to find similarities and dissimilarities in data-driven process models among U.S. Veterans Health Administration (VHA) facilities to assess process conformance among different healthcare facilities, which can help assess the standardization of care. We illustrate our approach by applying it to two clinical radiology order process models generated by two similar facilities. Our results demonstrate statistical similarities in the standardization of care among those two facilities.

Klasky, Hilda↗

Transfer of terrestrial technology for lunar mining

The functions, operational procedures, and major items of equipment that comprise the terrestrial mining process are characterized. These data are used to synthesize a similar activity on the lunar surface. Functions, operations, and types of equipment that can be suitably transferred to lunar operation are identified. Shortfalls, enhancements, and technology development needs are described. The lunar mining process and what is required to adapt terrestrial equipment are highlighted. It is concluded that translation of terrestrial mining equipment and operational processes to perform similar functions on the lunar surface is practical. Adequate attention must be given to the harsh environment and logistical constraints of the lunar setting. By using earth-based equipment as a forcing function, near- and long-term benefits are derived (i.e., improved terrestrial mining in the near term vis-a-vis commercial production of helium-3 in the long term.

Hall, Robert A.↗

Text Mining for Process–Structure–Properties Relationships in Metals

With the advent of large language models (LLMs), the vast unstructured text within millions of academic papers is increasingly accessible for materials discovery—although significant challenges remain. While LLMs offer promising few- and zero-shot learning capabilities, particularly valuable in the materials domain where expert annotations are scarce, general-purpose LLMs often fail to address key materials-specific queries without further adaptation. To bridge this gap, fine-tuning LLMs on human-labeled data is essential for effective structured knowledge extraction (Liu in The Importance of Human-Labeled Data in the Era of LLMs, 2023). Here, in this study, we introduce a novel annotation schema designed to extract generic process–structure–properties relationships from scientific literature. We demonstrate the utility of this approach using a dataset of 128 abstracts, with annotations drawn from two distinct domains: high-temperature materials (Domain I) and uncertainty quantification in simulating materials microstructure (Domain II). Initially, we developed a conditional random field (CRF) model based on MatBERT—a domain-specific BERT variant—and evaluated its performance on Domain I. Subsequently, we compared this model with a fine-tuned LLM (GPT-4o from OpenAI) under identical conditions. Our results indicate that fine-tuning LLMs can significantly improve entity extraction performance over the BERT-CRF baseline on Domain I. However, when additional examples from Domain II were incorporated, the performance of the BERT-CRF model became comparable to that of the GPT-4o model. These findings underscore the potential of our schema for structured knowledge extraction and highlight the complementary strengths of both modeling approaches.

Materials science↗

Baseline studies on the feasibility of detecting a coal/shale interface with a self-powered sensitized pick

The feasibility of utilizing a sensitized pick to discriminate between cutting coal and roof material during the longwall mining process was investigated. A conventional longwall mining pick was instrumented and cutting force magnitudes were determined for a variety of materials, including Illinois #6 coal, shale type materials, and synthetic coal/shale materials.

Anderson, G. R., II↗

The National Laboratory of the Rockies Strengthens U.S. Critical Minerals Supply Chains

The National Laboratory of the Rockies (NLR) is working to overcome bottlenecks and secure the U.S. critical mineral supply chain - delivering lower-cost, lower-risk pathways from unconventional and secondary feedstocks to validated products. NLR achieves this through cross-sector partnerships to advance U.S. critical minerals across the mining, processing, manufacturing, usage, and end-of-life stages.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A methodology for the environmental assessment of advanced coal extraction systems

Procedures developed to identify and assess potential environment impacts of advanced mining technology as it moves from a generic concept to a more systems definition are described. Two levels of assessment are defined in terms of the design stage of the technology being evaluated. The first level of analysis is appropriate to a conceptual design. At this level it is assumed that each mining process has known and potential environmental impacts that are generic to each mining activity. By using this assumption, potential environmental impacts can be identified for new mining systems. When two or more systems have been assessed, they can be evaluated comparing potential environmental impacts. At the preliminary stage of design, a systems performance can be assessed again with more precision. At this level of systems definition, potential environmental impacts can be analyzed and their significane determined in a manner to facilitate comparisons between systems. At each level of analysis, suggestions calculated to help the designer mitigate potentially harmful impacts are provided.

Sullivan, P. J.↗

Six Machine-Learning Methods for Predicting Hospital-Stay Duration for Patients with Sepsis: A Comparative Study

Sepsis is a life-threatening medical condition that, if not treated promptly, can result in tissue damage, organ failure, and death. According to the Centers for Disease Control, about 270,000 individuals die of sepsis in the US each year. Further, sepsis expenditures accounted for 13% of total US hospital costs in 2013, totaling more than $24 billion. Our project objectives were to determine if Machine Learning algorithms could reliably predict hospital stay duration for patients with sepsis. The data set we used has been de-identified and is freely available through the BupaR package. The data includes 1050 cases, 15214 events, and 16 types of actions related to sepsis patient care. First, we used process mining to determine how long each patient was in the hospital. Using BupaR’s functions, we created several process model graphs. These process models depict the movement of patients at a hospital and provide duration data for each patent case. Second, we identified outlier data and created two dataset versions: one with and one without outliers. We then applied the following analysis methods: Linear Regression, Random Forest, K-Nearest Neighbors, Neural Networks, XGBoost, and lightGBM. We compared the model validations for the six machine learning models using the same data-splitting method. We found that the XGBoost model had the best prediction accuracy of 73.9 percent for cases with outliers, and 79 percent for cases without outliers. We also found that the lightGBM model had the lowest mean absolute error between prediction and actual duration in days with 3.66 days for the case with outliers, and 2.4 days for the case without outliers. These two models outperformed the other four models. This work will be enhanced in the future by exploring new prediction algorithms and comparing them with the results of this study.

Chen, Lingtao↗

Reduction and potential remediation of U(VI) by dithionite at an in-situ recovery mine: Insights gained by δ 238 U

In-situ recovery is a common method of mining U ore. This technique involves injecting an oxidant to oxidize U deposited as insoluble U(IV) to soluble U(VI) and a complexing agent to form mobile U(VI) compounds, which are extracted from mining waters. Unfortunately, U concentrations often remain elevated in groundwater following this mining process. One promising technique to decrease U concentrations to acceptable levels is in-situ remediation where a reductant is injected into the mined area to reduce U(VI) back to insoluble U(IV). Here we assess the efficacy of the chemical reductant dithionite to reduce U(VI) concentrations. While dithionite can reduce environmental Cr(VI), dithionite has previously never been tested for reducing U(VI) in the environment. We determine how effectively dithionite remediates U(VI) contamination using aqueous U concentration and δ 238 U data. U concentrations and δ 238 U decrease during the dithionite experiment, demonstrating that dithionite induces U(VI) reduction. As dithionite is removed by pumping, U concentrations and δ 238 U increase towards background levels, but U(VI) reduction continues for an extended period. In conclusion, measurements demonstrate that re-oxidation and remobilization does not appear to occur due to the reducing condition of groundwater.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗