Contributions and limitations of using machine learning to predict noise-induced hearing loss

Purpose Noise-induced hearing loss (NIHL) is a global issue that impacts people’s life and health. The current review aims to clarify the contributions and limitations of applying machine learning (ML) to predict NIHL by analyzing the performance of different ML techniques and the procedure of model construction. Methods The authors searched PubMed, EMBASE and Scopus on November 26, 2020. Results Eight studies were recruited in the current review following defined inclusion and exclusion criteria. Sample size in the selected studies ranged between 150 and 10,567. The most popular models were artificial neural networks (n = 4), random forests (n = 3) and support vector machines (n = 3). Features mostly correlated with NIHL and used in the models were: age (n = 6), duration of noise exposure (n = 5) and noise exposure level (n = 4). Five included studies used either split-sample validation (n = 3) or ten-fold cross-validation (n = 2). Assessment of accuracy ranged in value from 75.3% to 99% with a low prediction error/root-mean-square error in 3 studies. Only 2 studies measured discrimination risk using the receiver operating characteristic (ROC) curve and/or the area under ROC curve. Conclusion In spite of high accuracy and low prediction error of machine learning models, some improvement can be expected from larger sample sizes, multiple algorithm use, completed reports of model construction and the sufficient evaluation of calibration and discrimination risk

A Search for Propylene Oxide and Glycine in Sagittarius B2 (LMH) and Orion

We have used the Mopra Telescope to search for glycine and the simple chiral molecule propylene oxide in the Sgr B2 (LMH) and Orion KL, in the 3-mm band. We have not detected either species, but have been able to put sensitive upper limits on the abundances of both molecules. The 3-sigma upper limits derived for glycine conformer I are 3.7 x 10^{14} cm^{-2} in both Orion-KL and Sgr B2 (LMH), comparable to the reported detections of conformer I by Kuan et al. However, as our values are 3-sigma upper limits rather than detections we conclude that this weighs against confirming the detection of Kuan et al. We find upper limits for the glycine II column density of 7.7 x 10^{12} cm^{-2} in both Orion-KL and Sgr B2 (LMH), in agreement with the results of Combes et al. The results presented here show that glycine conformer II is not present in the extended gas at the levels detected by Kuan et al. for conformer I. Our ATCA results (Jones et al.) have ruled out the detection of glycine (both conformers I and II) in the compact hot core of the LMH at the levels reported, so we conclude that it is unlikely that Kuan et al. have detected glycine in either Sgr B2 or Orion-KL. We find upper limits for propylene oxide abundance of 3.0 x 10^{14} cm^{-2} in Orion-KL and 6.7 x 10^{14} cm^{-2} in Sgr B2 (LMH). We have detected fourteen features in Sgr B2 and four features in Orion-KL which have not previously been reported in the ISM, but have not be able to plausibly assign these transitions to any carrier.Comment: 12 pages, 3 figures. Accepted by MNRAS 12th January 200

Formation of nanoscale structures by inductively coupled plasma etching

This paper will review the top down technique of ICP etching for the formation of nanometer scale structures. The increased difficulties of nanoscale etching will be described. However it will be shown and discussed that inductively coupled plasma (ICP) technology is well able to cope with the higher end of the nanoscale: features from 100nm down to about 40nm are relatively easy with current ICP technology. It is the ability of ICP to operate at low pressure yet with high plasma density and low (controllable) DC bias that helps greatly compared to simple reactive ion etching (RIE) and, though continual feature size reduction is increasingly challenging, improvements to ICP technology as well as improvements in masking are enabling sub-10nm features to be reached. Nanoscale ICP etching results will be illustrated in a range of materials and technologies. Techniques to facilitate etching (such as the use of cryogenic temperatures) and techniques to improve the mask performance will be described and illustrated

Machine learning in diagnosing middle ear disorders using tympanic membrane images : a meta-analysis

OBJECTIVE : To systematically evaluate the development of Machine Learning (ML) models and compare their diagnostic accuracy for the classification of Middle Ear Disorders (MED) using Tympanic Membrane (TM) images. METHODS : PubMed, EMBASE, CINAHL, and CENTRAL were searched up until November 30, 2021. Studies on the development of ML approaches for diagnosing MED using TM images were selected according to the inclusion criteria. PRISMA guidelines were followed with study design, analysis method, and outcomes extracted. Sensitivity, specificity, and area under the curve (AUC) were used to summarize the performance metrics of the meta-analysis. Risk of Bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool in combination with the Prediction Model Risk of Bias Assessment Tool. RESULTS : Sixteen studies were included, encompassing 20254 TM images (7025 normal TM and 13229 MED). The sample size ranged from 45 to 6066 per study. The accuracy of the 25 included ML approaches ranged from 76.00% to 98.26%. Eleven studies (68.8%) were rated as having a low risk of bias, with the reference standard as the major domain of high risk of bias (37.5%). Sensitivity and specificity were 93% (95% CI, 90%–95%) and 85% (95% CI, 82%–88%), respectively. The AUC of total TM images was 94% (95% CI, 91%–96%). The greater AUC was found using otoendoscopic images than otoscopic images. CONCLUSIONS : ML approaches perform robustly in distinguishing between normal ears and MED, however, it is proposed that a standardized TM image acquisition and annotation protocol should be developed.NIHR, Sêr Cymru III Enhancing Competitiveness Infrastructure Award, Great Britain Sasakawa Foundation, Cardiff Metropolitan University Research Innovation Award, and The Global Academies Research and Innovation Development Fund, National Natural Science Foundation of China, Guizhou Provincial Science and Technology Projects and Global Academies and Santandar 2021 Fellowship Award.https://onlinelibrary.wiley.com/journal/15314995am2024Electrical, Electronic and Computer EngineeringSpeech-Language Pathology and AudiologySDG-03:Good heatlh and well-beingSDG-09: Industry, innovation and infrastructur

Formation of nanoscale structures by inductively coupled plasma etching

This paper will review the top down technique of ICP etching for the formation of nanometer scale structures. The increased difficulties of nanoscale etching will be described. However it will be shown and discussed that inductively coupled plasma (ICP) technology is well able to cope with the higher end of the nanoscale: features from 100nm down to about 40nm are relatively easy with current ICP technology. It is the ability of ICP to operate at low pressure yet with high plasma density and low (controllable) DC bias that helps greatly compared to simple reactive ion etching (RIE) and, though continual feature size reduction is increasingly challenging, improvements to ICP technology as well as improvements in masking are enabling sub-10nm features to be reached. Nanoscale ICP etching results will be illustrated in a range of materials and technologies. Techniques to facilitate etching (such as the use of cryogenic temperatures) and techniques to improve the mask performance will be described and illustrated

Intramyocardial Injection of a Synthetic Hydrogel with Delivery of bFGF and IGF1 in a Rat Model of Ischemic Cardiomyopathy

It is increasingly appreciated that the properties of a biomaterial used in intramyocardial injection therapy influence the outcomes of infarcted hearts that are treated. In this report the extended in vivo efficacy of a thermally responsive material that can deliver dual growth factors while providing a slow degradation time and high mechanical stiffness is examined. Copolymers consisting of <i>N</i>-isopropylacrylamide, 2-hydroxyethyl methacrylate, and degradable methacrylate polylactide were synthesized. The release of bioactive basic fibroblast growth factor (bFGF) and insulin-like growth factor 1 (IGF1) from the gel and loaded poly­(lactide-<i>co</i>-glycolide) microparticles was assessed. Hydrogel with or without loaded growth factors was injected into 2 week-old infarcts in Lewis rats and animals were followed for 16 weeks. The hydrogel released bioactive bFGF and IGF1 as shown by mitogenic effects on rat smooth muscle cells in vitro. Cardiac function and geometry were improved for 16 weeks after hydrogel injection compared to saline injection. Despite demonstrating that left ventricular levels of bFGF and IGF1 were elevated for two weeks after injection of growth factor loaded gels, both functional and histological assessment showed no added benefit to inclusion of these proteins. This result points to the complexity of designing appropriate materials for this application and suggests that the nature of the material alone, without exogenous growth factors, has a direct ability to influence cardiac remodeling