Quantifying Analysis of Uncertainty in Medical Reporting: Creation of User and Context-Specific Uncertainty Profiles

Degree of Uncertainty in Reporting Imaging Findings for Necrotizing Enterocolitis: A Secondary Analysis from a Pilot Randomized Diagnostic Trial

Diagnosis of necrotizing enterocolitis (NEC) relies heavily on imaging, but uncertainty in the language used in imaging reports can result in ambiguity, miscommunication, and potential diagnostic errors. To determine the degree of uncertainty in reporting imaging findings for NEC, we conducted a secondary analysis of the data from a previously completed pilot diagnostic randomized controlled trial (2019-2020). The study population comprised sixteen preterm infants with suspected NEC randomized to abdominal radiographs (AXRs) or AXR + bowel ultrasound (BUS). The level of uncertainty was determined using a four-point Likert scale. Overall, we reviewed radiology reports of 113 AXR and 24 BUS from sixteen preterm infants with NEC concern. The BUS reports showed less uncertainty for reporting pneumatosis, portal venous gas, and free air compared to AXR reports (pneumatosis: 1 [1-1.75) vs. 3 [2-3], p < 0.0001; portal venous gas: 1 [1-1] vs. 1 [1-1], p = 0.02; free air: 1 [1-1] vs. 2 [1-3], p < 0.0001). In conclusion, we found that BUS reports have a lower degree of uncertainty in reporting imaging findings of NEC compared to AXR reports. Whether the lower degree of uncertainty of BUS reports positively impacts clinical decision making in infants with possible NEC remains unknown.

Theory of radiologist interaction with instant messaging decision support tools: A sequential-explanatory study

Radiology specific clinical decision support systems (CDSS) and artificial intelligence are poorly integrated into the radiologist workflow. Current research and development efforts of radiology CDSS focus on 4 main interventions, based around exam centric time points-after image acquisition, intra-report support, post-report analysis, and radiology workflow adjacent. We review the literature surrounding CDSS tools in these time points, requirements for CDSS workflow augmentation, and technologies that support clinician to computer workflow augmentation. We develop a theory of radiologist-decision tool interaction using a sequential explanatory study design. The study consists of 2 phases, the first a quantitative survey and the second a qualitative interview study. The phase 1 survey identifies differences between average users and radiologist users in software interventions using the User Acceptance of Information Technology: Toward a Unified View (UTAUT) framework. Phase 2 semi-structured interviews provide narratives on why these differences are found. To build this theory, we propose a novel solution called Radibot-a conversational agent capable of engaging clinicians with CDSS as an assistant using existing instant messaging systems supporting hospital communications. This work contributes an understanding of how radiologist-users differ from the average user and can be utilized by software developers to increase satisfaction of CDSS tools within radiology.

Conceptualising, evaluating and communicating uncertainty in forensic science: Identifying commonly used tools through an interdisciplinary configurative review

This study provides a set of tools for conceptualising, evaluating and communicating uncertainty in forensic science. Given that the concept of uncertainty is one that transcends disciplinary boundaries, an interdisciplinary configurative review was carried out incorporating the disciplines of medicine, environmental science and economics, in order to identify common themes which could have valuable applications to the discipline of forensic science. Critical Interpretive Synthesis was used to develop sub-synthetic and synthetic constructs which interpreted and synthesised the underlying evidence and codes. This study provides three toolkits, one each for conceptualisation, evaluation and communication. The study identified an underlying theme concerning the obstacles that would need to be overcome for the effective application of these toolkits and achieving effective conceptualisation, evaluation and communication of uncertainty in forensic science to lay-stakeholders. These toolkits offer a starting point for developing the conversation for achieving greater transparency in the communication of uncertainty. They also have the potential to offer stakeholders enhanced understanding of the nuances and limitations of forensic science evidence and enable more transparent evaluation and scrutiny of the reliability, relevance and probative value of forensic materials in a crime reconstruction.

A bibliometric analysis and visualization of medical data mining research

BACKGROUND

Data mining technology used in the field of medicine has been widely studied by scholars all over the world. But there is little research on medical data mining (MDM) from the perspectives of bibliometrics and visualization, and the research topics and development trends in this field are still unclear.

METHODS

This paper has applied bibliometric visualization software tools, VOSviewer 1.6.10 and CiteSpace V, to study the citation characteristics, international cooperation, author cooperation, and geographical distribution of the MDM.

RESULTS

A total of 1575 documents are obtained, and the most frequent document type is article (1376). SHAN NH is the most productive author, with the highest number of publications of 12, and the Gillies's article (750 times citation) is the most cited paper. The most productive country and institution in MDM is the USA (559) and US FDA (35), respectively. The Journal of Biomedical Informatics, Expert Systems with Applications and Journal of Medical Systems are the most productive journals, which reflected the nature of the research, and keywords "classification (790)" and "system (576)" have the strongest strength. The hot topics in MDM are drug discovery, medical imaging, vaccine safety, and so on. The 3 frontier topics are reporting system, precision medicine, and inflammation, and would be the foci of future research.

CONCLUSION

The present study provides a panoramic view of data mining methods applied in medicine by visualization and bibliometrics. Analysis of authors, journals, institutions, and countries could provide reference for researchers who are fresh to the field in different ways. Researchers may also consider the emerging trends when deciding the direction of their study.