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Journal of Dentistry Jun 2024To assess quality, clinical acceptance, time-efficiency, and consistency of a novel artificial intelligence (AI)-driven tool for automated presurgical implant planning...
OBJECTIVES
To assess quality, clinical acceptance, time-efficiency, and consistency of a novel artificial intelligence (AI)-driven tool for automated presurgical implant planning for single tooth replacement, compared to a human intelligence (HI)-based approach.
MATERIALS AND METHODS
To validate a novel AI-driven implant placement tool, a dataset of 10 time-matching cone beam computed tomography (CBCT) scans and intra-oral scans (IOS) previously acquired for single mandibular molar/premolar implant placement was included. An AI pre-trained model for implant planning was compared to human expert-based planning, followed by the export, evaluation and comparison of two generic implants-AI-generated and human-generated-for each case. The quality of both approaches was assessed by 12 calibrated dentists through blinded observations using a visual analogue scale (VAS), while clinical acceptance was evaluated through an AI versus HI battle (Turing test). Subsequently, time efficiency and consistency were evaluated and compared between both planning methods.
RESULTS
Overall, 360 observations were gathered, with 240 dedicated to VAS, of which 95 % (AI) and 96 % (HI) required no major, clinically relevant corrections. In the AI versus HI Turing test (120 observations), 4 cases had matching judgments for AI and HI, with AI favoured in 3 and HI in 3. Additionally, AI completed planning more than twice as fast as HI, taking only 198 ± 33 s compared to 435 ± 92 s (p < 0.05). Furthermore, AI demonstrated higher consistency with zero-degree median surface deviation (MSD) compared to HI (MSD=0.3 ± 0.17 mm).
CONCLUSION
AI demonstrated expert-quality and clinically acceptable single-implant planning, proving to be more time-efficient and consistent than the HI-based approach.
CLINICAL SIGNIFICANCE
Presurgical implant planning often requires multidisciplinary collaboration between highly experienced specialists, which can be complex, cumbersome and time-consuming. However, AI-driven implant planning has the potential to allow clinically acceptable planning, significantly more time-efficient and consistent than the human expert.
PubMed: 38914182
DOI: 10.1016/j.jdent.2024.105146 -
PloS One 2024Chemical contamination and pollution are an ongoing threat to human health and the environment. The concern over the consequences of chemical exposures at the global...
INTRODUCTION
Chemical contamination and pollution are an ongoing threat to human health and the environment. The concern over the consequences of chemical exposures at the global level continues to grow. Because resources are constrained, there is a need to prioritize interventions focused on the greatest health impact. Data, especially related to chemical exposures, are rarely available for most substances of concern, and alternate methods to evaluate their impact are needed.
STRUCTURED EXPERT JUDGMENT (SEJ) PROCESS
A Structured Expert Judgment (Research Outreach, 2021) process was performed to provide plausible estimates of health impacts for 16 commonly found pollutants: asbestos, arsenic, benzene, chromium, cadmium, dioxins, fluoride, highly hazardous pesticides (HHPs), lead, mercury, polycyclic-aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), Per- and Polyfluorinated Substances (PFAs), phthalates, endocrine disrupting chemicals (EDCs), and brominated flame retardants (BRFs). This process, undertaken by sector experts, weighed individual estimations of the probable global health scale health impacts of each pollutant using objective estimates of the expert opinions' statistical accuracy and informativeness.
MAIN FINDINGS
The foremost substances, in terms of mean projected annual total deaths, were lead, asbestos, arsenic, and HHPs. Lead surpasses the others by a large margin, with an estimated median value of 1.7 million deaths annually. The three other substances averaged between 136,000 and 274,000 deaths per year. Of the 12 other chemicals evaluated, none reached an estimated annual death count exceeding 100,000. These findings underscore the importance of prioritizing available resources on reducing and remediating the impacts of these key pollutants.
RANGE OF HEALTH IMPACTS
Based on the evidence available, experts concluded some of the more notorious chemical pollutants, such as PCBs and dioxin, do not result in high levels of human health impact from a global scale perspective. However, the chemical toxicity of some compounds released in recent decades, such as Endocrine Disrupters and PFAs, cannot be ignored, even if current impacts are limited. Moreover, the impact of some chemicals may be disproportionately large in some geographic areas. Continued research and monitoring are essential; and a preventative approach is needed for chemicals.
FUTURE DIRECTIONS
These results, and potential similar analyses of other chemicals, are provided as inputs to ongoing discussions about priority setting for global chemicals and pollution management. Furthermore, we suggest that this SEJ process be repeated periodically as new information becomes available.
Topics: Humans; Environmental Pollutants; Environmental Exposure; Expert Testimony; Endocrine Disruptors; Pesticides; Polychlorinated Biphenyls; Arsenic; Polycyclic Aromatic Hydrocarbons; Environmental Pollution; Asbestos; Dioxins
PubMed: 38913645
DOI: 10.1371/journal.pone.0298504 -
The American Journal of Bioethics : AJOB Jul 2024
Topics: Humans; Coercion; Patient Preference; Judgment; Artificial Intelligence; Decision Making
PubMed: 38913476
DOI: 10.1080/15265161.2024.2353820 -
JMIR Serious Games Jun 2024Pressure ulcers (PUs) are a common and serious complication in patients who are immobile in health care settings. Nurses play a fundamental role in the prevention of...
BACKGROUND
Pressure ulcers (PUs) are a common and serious complication in patients who are immobile in health care settings. Nurses play a fundamental role in the prevention of PUs; however, novice nurses lack experience in clinical situations. Virtual reality (VR) is highly conducive to clinical- and procedure-focused training because it facilitates simulations.
OBJECTIVE
We aimed to explore the feasibility of a novel PU management VR simulation (PU-VRSim) program using a head-mounted display for novice nurses and to investigate how different types of learning materials (ie, VR or a video-based lecture) impact learning outcomes and experiences.
METHODS
PU-VRSim was created in the Unity 3D platform. This mixed methods pilot quasi-experimental study included 35 novice nurses categorized into the experimental (n=18) and control (n=17) groups. The PU-VRSim program was applied using VR in the experimental group, whereas the control group received a video-based lecture. The PU knowledge test, critical thinking disposition measurement tool, and Korean version of the General Self-Efficacy Scale were assessed before and after the intervention in both groups. After the intervention, the experimental group was further assessed using the Clinical Judgment Rubric and interviewed to evaluate their experience with PU-VRSim.
RESULTS
The results compared before and after the intervention showed significant improvements in PU knowledge in both the experimental group (P=.001) and control group (P=.005). There were no significant differences in self-efficacy and critical thinking in either group. The experimental group scored a mean of 3.23 (SD 0.44) points (accomplished) on clinical judgment, assessed using a 4-point scale. The experimental group interviews revealed that the VR simulation was realistic and helpful for learning about PU management.
CONCLUSIONS
The results revealed that PU-VRSim could improve novice nurses' learning of PU management in realistic environments. Further studies using VR for clinical training are recommended for novice nurses.
PubMed: 38913417
DOI: 10.2196/53165 -
[Nihon Koshu Eisei Zasshi] Japanese... Jun 2024Objective To decrease cancer mortality by implementing cancer screening programs, rigorous quality control measures that utilize standardized indicators are...
Objective To decrease cancer mortality by implementing cancer screening programs, rigorous quality control measures that utilize standardized indicators are imperative. In Japan, although each municipality performing cancer screening programs implements quality control for their programs using the checklist authorized by the Ministry of Health, Labour and Welfare, compliance with all the items listed is not possible because calculating sensitivity and specificity using cancer registry data is difficult under these circumstances. This report elucidates the methodology for calculating indicators, including sensitivity and specificity, by delineating the parameters of false-negative cases within population-based cancer screening programs in Japan. Furthermore, the inherent challenges associated with ensuring the quality control of cancer screening procedures are expounded upon in this report.Method Data from the Prefectural Cancer Registry of Japan and cancer screening records compiled by municipalities were used to differentiate true-positive, true-negative, false-positive, and false-negative cases based on the combination of screening test outcomes and subsequent cancer incidence.Results A false-negative case was defined as an examinee who received a cancer diagnosis within one year after undergoing the screening test, notwithstanding the negative judgment of the cancer screening decision. The duration for judgment of true-positive, true-negative, and false-negative cases was also extended to one year. Cancer identification after cancer screening was ascertained using data from the Prefectural Cancer Registry, ensuring uniform categorization of the four cases. Subsequently, sensitivity and specificity values were calculated for municipalities conducting cancer screening programs.Conclusion Sensitivity and specificity are indispensable metrics for the inherent quality control of cancer screening because these parameters directly assess the efficacy of screening tests. The anticipated increase in the number of municipalities engaged in comprehensive quality control of cancer screening in Japan is poised to enhance the efficiency of cancer control policies. This augmentation will be accomplished through the meticulous utilization of the sensitivity and specificity values elucidated in the present report. The forthcoming challenges involve the proliferation of medical institutes reporting their adherence to the checklist stipulated by the National Cancer Center of Japan and the widespread dissemination of fundamental knowledge pertaining to cancer screening.
PubMed: 38910126
DOI: 10.11236/jph.23-107 -
La Revue de Medecine Interne Jun 2024Many patients with cancer require palliative care at some stage and the vast majority of people followed in palliative care are cancer patients. Patients with cancer are... (Review)
Review
Many patients with cancer require palliative care at some stage and the vast majority of people followed in palliative care are cancer patients. Patients with cancer are at high risk of venous thromboembolism (VTE), and this is particularly true during the advanced palliative phase when mobility is limited or absent. Patients with cancer in palliative care are at higher bleeding risk compared to non-cancer patients. Decisions to treat VTE or withhold anticoagulation for these patients have proven to be difficult and depend largely on an individual clinician's judgment. For this reason, we have developed a consensus proposal for appropriate management of cancer-associated thromboembolism (CAT) in patients in palliative care, which is presented in this article. The proposal was informed by the recent scientific literature retrieved through a systematic literature review. In cancer patients in advanced palliative care, the benefit/risk ratio of anticoagulation seems unfavourable with a higher haemorrhagic risk than the benefit associated with prevention of CAT recurrence and, above all, in the absence of any benefit on quality of life. For this reason, we recommend that patients should be prescribed anticoagulants on a case-by-case basis. The choice of whether to treat, and with which type of treatment, should take into account anticipated life expectancy and patient preferences, as well as clinical factors such as the estimated bleeding risk, the type of VTE experienced and the time since the VTE event.
PubMed: 38908989
DOI: 10.1016/j.revmed.2024.06.001 -
The Science of the Total Environment Jun 2024Assessment of occupational exposure to viruses is crucial to identify virus reservoirs and sources of dissemination at an early stage and to help prevent spread between... (Review)
Review
Assessment of occupational exposure to viruses is crucial to identify virus reservoirs and sources of dissemination at an early stage and to help prevent spread between employees and to the general population. Measuring workers' exposure can facilitate assessment of the effectiveness of protective and mitigation measures in place. The aim of this scoping review is to give an overview of available methods and those already implemented for airborne virus' exposure assessment in different occupational and indoor environments. The results retrieved from the different studies may contribute to the setting of future standards and guidelines to ensure a reliable risk characterization in the occupational environments crucial for the implementation of effective control measures. The search aimed at selecting studies between January 1st 2010 and June 30th 2023 in the selected databases. Fifty papers on virus exposure assessment fitted the eligibility criteria and were selected for data extraction. Overall, this study identified gaps in knowledge regarding virus assessment and pinpointed the needs for further research. Several discrepancies were found (transport temperatures, elution steps, …), as well as a lack of publication of important data related to the exposure conditions (contextual information). With the available information, it is impossible to compare results between studies employing different methods, and even if the same methods are used, different conclusions/recommendations based on the expert judgment have been reported due to the lack of consensus in the contextual information retrieved and/or data interpretation. Future research on the field targeting sampling methods and in the laboratory regarding the assays to employ should be developed bearing in mind the different goals of the assessment.
PubMed: 38908595
DOI: 10.1016/j.scitotenv.2024.174016 -
Current Opinion in Psychology Jun 2024Facial inference, a cornerstone of person perception, has traditionally been studied through human judgments about personality traits and abilities based on people's... (Review)
Review
Facial inference, a cornerstone of person perception, has traditionally been studied through human judgments about personality traits and abilities based on people's faces. Recent advances in artificial intelligence (AI) have introduced new dimensions to this field, employing machine learning algorithms to reveal people's character, capabilities, and social outcomes based just on their faces. This review examines recent research on human and AI-based facial inference across psychology, business, computer science, legal, and policy studies to highlight the need for scientific consensus on whether or not people's faces can reveal their inner traits, and urges researchers to address the critical concerns around epistemic validity, practical relevance, and societal welfare before recommending AI-based facial inference for consequential uses.
PubMed: 38908348
DOI: 10.1016/j.copsyc.2024.101815 -
The American Journal of Emergency... Jun 2024Emergency department (ED) overcrowding presents a global challenge that inhibits prompt care for critically ill patients. Traditional 5-level triage system that heavily...
OBJECTIVES
Emergency department (ED) overcrowding presents a global challenge that inhibits prompt care for critically ill patients. Traditional 5-level triage system that heavily rely on the judgment of the triage staff could fail to detect subtle symptoms in critical patients, thus leading to delayed treatment. Unlike previous rivalry-focused approaches, our study aimed to establish a collaborative machine learning (ML) model that renders risk scores for severe illness, which may assist the triage staff to provide a better patient stratification for timely critical cares.
METHODS
This retrospective study was conducted at a tertiary teaching hospital. Data were collected from January 2015 to October 2022. Demographic and clinical information were collected at triage. The study focused on severe illness as the outcome. We developed artificial neural network (ANN) models, with or without utilizing the Taiwan Triage and Acuity Scale (TTAS) score as one of the predictors. The model using the TTAS score is termed a machine-human collaborative model (ANN-MH), while the model without it is referred to as a machine-only model (ANN-MO). The predictive power of these models was assessed using the area under the receiver-operating-characteristic (AUROC) and the precision-recall curves (AUPRC); their sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1 score were compared.
RESULTS
The study analyzed 668,602 ED visits from 2015 to 2022. Among them, 278,724 visits from 2015 to 2018 were used for model training and validation, while 320,201 visits from 2019 to 2022 were for testing model performance. Approximately 2.6% of visits were by severely ill patients, whose TTAS scores ranged from 1 to 5. The ANN-MH model achieved a testing AUROC of 0.918 and AUPRC of 0.369, while for the ANN-MO model the AUROC and AUPRC were 0.909 and 0.339, respectively. Based on these metrics, the ANN-MH model outperformed the ANN-MO model, and both surpassed human triage classification. Subgroup analyses further highlighted the models' capability to identify higher-risk patients within the same triage level.
CONCLUSIONS
The traditional 5-level triage system often falls short, leading to under-triage of critical patients. Our models include a score-based differentiation within a triage level to offer advanced risk stratification, thereby promoting patient safety.
PubMed: 38908339
DOI: 10.1016/j.ajem.2024.06.015 -
Cognition Jun 2024Rules help guide our behavior-particularly in complex social contexts. But rules sometimes give us the "wrong" answer. How do we know when it is okay to break the rules?...
Rules help guide our behavior-particularly in complex social contexts. But rules sometimes give us the "wrong" answer. How do we know when it is okay to break the rules? In this paper, we argue that we sometimes use contractualist (agreement-based) mechanisms to determine when a rule can be broken. Our model draws on a theory of social interactions - "virtual bargaining" - that assumes that actors engage in a simulated bargaining process when navigating the social world. We present experimental data which suggests that rule-breaking decisions are sometimes driven by virtual bargaining and show that these data cannot be explained by more traditional rule-based or outcome-based approaches.
PubMed: 38908304
DOI: 10.1016/j.cognition.2024.105790