- Machine learning assessment of myocardial ischemia using angiography: Development and retrospective validation. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002693
- CONCLUSIONS: We found that angiography-based ML is useful to predict subtended myocardial territories and ischemia-producing lesions by mitigating the visual-functional mismatch between angiographic and FFR. Assessment of clinical utility requires further validation in a large, prospective cohort study.
- Machine learning to identify pairwise interactions between specific IgE antibodies and their association with asthma: A cross-sectional analysis within a population-based birth cohort. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002691
- CONCLUSIONS: Interactions between pairs of sIgE components are associated with increased risk of asthma and may provide the basis for designing diagnostic tools for asthma.
- Transforming health policy through machine learning. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002692
- In their Perspective, Ara Darzi and Hutan Ashrafian give us a tour of the future policymaker's machine learning toolkit.
In their Perspective, Ara Darzi and Hutan Ashrafian give us a tour of the future policymaker's machine learning toolkit.
- Safety, tolerability, and pharmacokinetics of long-acting injectable cabotegravir in low-risk HIV-uninfected individuals: HPTN 077, a phase 2a randomized controlled trial. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002690
- CONCLUSIONS: In this study, CAB LA was well tolerated at the doses and dosing intervals used. ISRs were common, but infrequently led to product discontinuation. CAB LA 600 mg every 8 weeks met pharmacokinetic targets for both male and female study participants. The safety and pharmacokinetic results observed support the further development of CAB LA, and efficacy studies of CAB LA for HIV treatment and prevention are in progress.
- Hydrometeorology and flood pulse dynamics drive diarrheal disease outbreaks and increase vulnerability to climate change in surface-water-dependent populations: A retrospective analysis. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002688
- CONCLUSIONS: In flood pulse river-floodplain systems, hydrology and water quality dynamics can be highly variable, potentially impacting conventional water treatment facilities and the production of safe drinking water. In Southern Africa, climate change is predicted to intensify hydrological variability and the frequency of extreme weather events, amplifying the public health threat of waterborne disease in surface-water-dependent populations. Water sector development should be prioritized with urgency, incorporating technologies that are robust to local environmental conditions and expected climate-driven impacts. In populations with high HIV burdens, expansion of diarrheal disease surveillance and intervention strategies may also be needed. As annual flood pulse processes are predominantly influenced by climate controls in distant regions, country-level data may be inadequate to refine predictions of climate-health interactions in these systems.
- Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002683
- CONCLUSIONS: Pneumonia-screening CNNs achieved better internal than external performance in 3 out of 5 natural comparisons. When models were trained on pooled data from sites with different pneumonia prevalence, they performed better on new pooled data from these sites but not on external data. CNNs robustly identified hospital system and department within a hospital, which can have large differences in disease burden and may confound predictions.
- Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002674
- CONCLUSIONS: To our knowledge, this study, for the first time, used large-scale data collected from electronic health records to demonstrate the contribution of big data and machine learning approaches to improved prediction of myopia prognosis in Chinese school-aged children. This work provides evidence for transforming clinical practice, health policy-making, and precise individualised interventions regarding the practical control of school-aged myopia.
- Machine learning in medicine: Addressing ethical challenges. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002689
- Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.
Effy Vayena and colleagues argue that machine learning in medicine must offer data protection, algorithmic transparency, and accountability to earn the trust of patients and clinicians.
- Lymphopenia and risk of infection and infection-related death in 98,344 individuals from a prospective Danish population-based study. [Journal Article]
- PMPLoS Med 2018; 15(11):e1002685
- CONCLUSIONS: Lymphopenia was associated with increased risk of hospitalization with infection and increased risk of infection-related death in the general population. Notably, causality cannot be deduced from our data.
New Search Next
- Correction: Signatures of inflammation and impending multiple organ dysfunction in the hyperacute phase of trauma: A prospective cohort study. [Published Erratum]
- PMPLoS Med 2018; 15(10):e1002694
- [This corrects the article DOI: 10.1371/journal.pmed.1002352.].
[This corrects the article DOI: 10.1371/journal.pmed.1002352.].