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The intramembrane protease SPPL2c promotes male germ cell development by cleaving phospholamban
(2019)
The clinical and biological significance of MIR-224 expression in colorectal cancer metastasis
(2015)
To the Editor: Artificial intelligence (AI) has shown promise for improving diagnostics of skin cancer by matching or surpassing experienced clinicians.1 However, the successful clinical application depends on acceptance by patients and dermatologists.
In this prospective multicentric survey study with a response rate of 63%, we therefore investigate the criteria required for patients and dermatologists to accept AI-systems and assess their importance on patients’ and dermatologists’ decision-making when considering the use of such systems. To this end, we perform an adaptive choice-based conjoint analysis and analyze it using hierarchical Bayes estimation.2 By employing an adaptive choice-based conjoint analysis, we investigate multiple influencing AI-features simultaneously (see Table I) whilst accounting for possible trade-offs (see Fig 1). For details on questionnaire development, participant recruitment, and statistical analysis, see Supplementary Methods, available via Mendeley at https://data.mendeley.com/datasets/2chcwnhpwj/1.
Background
There is limited knowledge of whether cognitive-behavioral therapy (CBT) or second-generation antipsychotics (SGAs) should be recommended as the first-line treatment in individuals at clinical high risk for psychosis (CHRp).
Hypothesis
To examine whether individual treatment arms are superior to placebo and whether CBT is non-inferior to SGAs in preventing psychosis over 12 months of treatment.
Study Design
PREVENT was a blinded, 3-armed, randomized controlled trial comparing CBT to clinical management plus aripiprazole (CM + ARI) or plus placebo (CM + PLC) at 11 CHRp services. The primary outcome was transition to psychosis at 12 months. Analyses were by intention-to-treat.
Study Results
Two hundred eighty CHRp individuals were randomized: 129 in CBT, 96 in CM + ARI, and 55 in CM + PLC. In week 52, 21 patients in CBT, 19 in CM + ARI, and 7 in CM + PLC had transitioned to psychosis, with no significant differences between treatment arms (P = .342). Psychopathology and psychosocial functioning levels improved in all treatment arms, with no significant differences.
Conclusions
The analysis of the primary outcome transition to psychosis at 12 months and secondary outcomes symptoms and functioning did not demonstrate significant advantages of the active treatments over placebo. The conclusion is that within this trial, neither low-dose aripiprazole nor CBT offered additional benefits over clinical management and placebo.
Performance measures are an important tool for assessing and comparing different medical image segmentation algorithms. Unfortunately, the current measures have their weaknesses when it comes to assessing certain edge cases. These limitations arise when images with a very small region of interest or without a region of interest at all are assessed. As a solution to these limitations, we propose a new medical image segmentation metric: MISm. This metric is a composition of the Dice similarity coefficient and the weighted specificity. MISm was investigated for definition gaps, an appropriate scoring gradient, and different weighting coefficients used to propose a constant value. Furthermore, an evaluation was performed by comparing the popular metrics in the medical image segmentation and MISm using images of magnet resonance tomography from several fictitious prediction scenarios. Our analysis shows that MISm can be applied in a general way and thus also covers the mentioned edge cases, which are not covered by other metrics, in a reasonable way. In order to allow easy access to MISm and therefore widespread application in the community, as well as reproducibility of experimental results, we included MISm in the publicly available evaluation framework MISeval.
