Rethinking PICO in the Machine Learning Era: ML-PICO

Background  Machine learning (ML) has captured the attention of many clinicians who may not have formal training in this area but are otherwise increasingly exposed to ML literature that may be relevant to their clinical specialties. ML papers that follow an outcomes-based research format can be assessed using clinical research appraisal frameworks such as PICO (Population, Intervention, Comparison, Outcome). However, the PICO frameworks strain when applied to ML papers that create new ML models, which are akin to diagnostic tests. There is a need for a new framework to help assess such papers. Objective  We propose a new framework to help clinicians systematically read and evaluate medical ML papers whose aim is to create a new ML model: ML-PICO (Machine Learning, Population, Identification, Crosscheck, Outcomes). We describe how the ML-PICO framework can be applied toward appraising literature describing ML models for health care. Conclusion  The relevance of ML to practitioners of clinical medicine is steadily increasing with a growing body of literature. Therefore, it is increasingly important for clinicians to be familiar with how to assess and best utilize these tools. In this paper we have described a practical framework on how to read ML papers that create a new ML model (or diagnostic test): ML-PICO. We hope that this can be used by clinicians to better evaluate the quality and utility of ML papers.     

Priming sentence comprehension in aphasia: effects of lexically independent and specific structural priming

Background & Aims: Impaired message-structure mapping results in deficits in both sentence production and comprehension in aphasia. Structural priming has been shown to facilitate syntactic production for persons with aphasia (PWA). However, it remains unknown if structural priming is also effective in sentence comprehension. We examined if PWA show preserved and lasting structural priming effects during interpretation of syntactically ambiguous sentences and if the priming effects occur independently of or in conjunction with lexical (verb) information.

Methods & Procedures: Eighteen PWA and 20 healthy older adults (HOA) completed a written sentence-picture matching task involving the interpretation of prepositional phrases (PP; the chef is poking the solider with an umbrella) that were ambiguous between high (verb modifier) and low attachment (object noun modifier). Only one interpretation was possible for prime sentences, while both interpretations were possible for target sentences. In Experiment 1, the target was presented immediately after the prime (0-lag). In Experiment 2, two filler items intervened between the prime and the target (2-lag). Within each experiment, the verb was repeated for half of the prime-target pairs, while different verbs were used for the other half. Participants’ off-line picture matching choices and response times were measured.

Results: After reading a prime sentence with a particular interpretation, HOA and PWA tended to interpret an ambiguous PP in a target sentence in the same way and with faster response times. Importantly, both groups continued to show this priming effect over a lag (Experiment 2), although the effect was not as reliable in response times. However, neither group showed lexical (verb-specific) boost on priming, deviating from robust lexical boost seen in the young adults of prior studies.

Conclusions: PWA demonstrate abstract (lexically-independent) structural priming in the absence of a lexically-specific boost. Abstract priming is preserved in aphasia, effectively facilitating not only immediate but also longer-lasting structure-message mapping during sentence comprehension.     

The discrepancy between verbal and visuoperceptual IQ in children with a specific learning disorder: An analysis of 1624 cases

Children with a specific learning disorder (SLD) are often characterized by marked intellectual strengths and weaknesses. In the last few years, research has focused on a common discrepancy between low working memory and processing speed on the one hand, and high verbal and visuoperceptual intelligence on the other. SLD profiles featuring a specific discrepancy between verbal and visuoperceptual abilities have been only marginally considered, however, and their systematic comparison vis-à-vis typically-developing (TD) populations has yet to be conducted. The present study examined a dataset of 1624 WISC-IV profiles of children with a diagnosis of SLD. It emerged that the proportion of children with a Verbal Comprehension Index (VCI) at least 1.5 SD (22 standardized points) lower than their scores on the Perceptual Reasoning Index (PRI) was larger than the proportion of SLD children with the opposite discrepant profile; it was also larger than the same proportion found among TD children. Comparing the two discrepant profiles revealed that the children also differed by type of learning difficulty, gender, and performance in the WISC-IV Symbol search task. Further examination suggested that children who were discrepant and also distinctly poor in visuoperceptual intelligence were particularly slow in general processing.     

儿童外科教学方法实践及探讨

目的探讨儿童外科的教学特点及教学方法,提高儿外科医生的总体执业水平,促进儿童外科学的发展。方法通过分析四川大学华西医院多年儿童外科疾病的临床教学实践经验,总结出适合医学生、初级儿童外科专科医生的实用的教学方法及经验。结果结合儿童外科特有的疾病特点所总结出的故事式讲述教学、典型病例教学、漫画形式学习、比较学习法及多媒体素材教学五种方式是非常适合儿童外科教学的方法。能够加深记忆,提高兴趣,轻松快捷,事半功倍的掌握相关医学专业知识。结论独特有趣的儿童外科教学方法可提高医学生及儿童外科初级从业者的学习兴趣、专业知识和执业水平。     

Multidimensional Ultrasound Doppler Signal Analysis for Fetal Activity Monitoring

Fetal activity parameters such as movements, heart rate and the related parameters are essential indicators of fetal wellbeing, and no device provides simultaneous access to and sufficient estimation of all of these parameters to evaluate fetal health. This work was aimed at collecting these parameters to automatically separate healthy from compromised fetuses. To achieve this goal, we first developed a multi-sensor–multi-gate Doppler system. Then we recorded multidimensional Doppler signals and estimated the fetal activity parameters via dedicated signal processing techniques. Finally, we combined these parameters into four sets of parameters (or four hyper-parameters) to determine the set of parameters that is able to separate healthy from other fetuses. To validate our system, a data set consisting of two groups of fetal signals (normal and compromised) was established and provided by physicians. From the estimated parameters, an instantaneous Manning-like score, referred to as the ultrasonic score, was calculated and was used together with movements, heart rate and the associated parameters in a classification process employing the support vector machine method. We investigated the influence of the sets of parameters and evaluated the performance of the support vector machine using the computation of sensibility, specificity, percentage of support vectors and total classification error. The sensitivity of the four sets ranged from 79% to 100%. Specificity was 100% for all sets. The total classification error ranged from 0% to 20%. The percentage of support vectors ranged from 33% to 49%. Overall, the best results were obtained with the set of parameters consisting of fetal movement, short-term variability, long-term variability, deceleration and ultrasound score. The sensitivity, specificity, percentage of support vectors and total classification error of this set were respectively 100%, 100%, 35% and 0%. This indicated our ability to separate the data into two sets (normal fetuses and pathologic fetuses), and the results highlight the excellent match with the clinical classification performed by the physicians. This work indicates the feasibility of detecting compromised fetuses and also represents an interesting method of close fetal monitoring during the entire pregnancy.