bluuebunny/crossref_metadata_2025_split huggingface dataset:
Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE)
Authors: Kelly Brendan S. , Judge Conor , Bollard Stephanie M. , Clifford Simon M. , Healy Gerard M. , Aziz Awsam , Mathur Prateek , Islam Shah , Yeom Kristen W. , Lawlor Aonghus , Killeen Ronan P. 
Published: April 2022

Abstract
Objective
There has been a large amount of research in the field of artificial intelligence (AI) as applied to clinical radiology. However, these studies vary in design and quality and systematic reviews of the entire field are lacking.This systematic review aimed to identify all papers that used deep learning in radiology to survey the literature and to evaluate their methods. We aimed to identify the key questions being addressed in the literature and to identify the most effective methods employed.

Methods
We followed the PRISMA guidelines and performed a systematic review of studies of AI in radiology published from 2015 to 2019. Our published protocol was prospectively registered.

Results
Our search yielded 11,083 results. Seven hundred sixty-seven full texts were reviewed, and 535 articles were included. Ninety-eight percent were retrospective cohort studies. The median number of patients included was 460. Most studies involved MRI (37%). Neuroradiology was the most common subspecialty. Eighty-eight percent used supervised learning. The majority of studies undertook a segmentation task (39%). Performance comparison was with a state-of-the-art model in 37%. The most used established architecture was UNet (14%). The median performance for the most utilised evaluation metrics was Dice of 0.89 (range .49–.99), AUC of 0.903 (range 1.00–0.61) and Accuracy of 89.4 (range 70.2–100). Of the 77 studies that externally validated their results and allowed for direct comparison, performance on average decreased by 6% at external validation (range increase of 4% to decrease 44%).

Conclusion
This systematic review has surveyed the major advances in AI as applied to clinical radiology.

Key Points
• While there are many papers reporting expert-level results by using deep learning in radiology, most apply only a narrow range of techniques to a narrow selection of use cases.
• The literature is dominated by retrospective cohort studies with limited external validation with high potential for bias.
• The recent advent of AI extensions to systematic reporting guidelines and prospective trial registration along with a focus on external validation and explanations show potential for translation of the hype surrounding AI from code to clinic.
Künstliche Intelligenz im Management der Anti-VEGF-Therapie: der „Vienna Fluid Monitor“ in der klinischen Praxis
Authors: Fuchs P. , Coulibaly L. , Reiter G. S. , Schmidt-Erfurth U. 
Published: April 2022

ZusammenfassungDer Vienna Fluid Monitor ist ein künstlicher Intelligenz(KI)-Algorithmus zur präzisen Lokalisation und Quantifizierung von retinaler Flüssigkeit. Der Algorithmus soll Klinikern und Klinikerinnen helfen, objektive und genaue Behandlungsentscheidungen bei der antivaskulären endothelialen Wachstumsfaktor(Anti-VEGF)-Therapie von Patienten mit neovaskulärer altersbedingter Makuladegeneration zu treffen. Ziel der Implementierung ist die Optimierung der Patientensicherheit, die Erhaltung der Sehleistung und gleichzeitig die Behandlungslast für das Gesundheitssystem und die Patienten zu verringern.
A prospective, multicenter, open-label study of the clinical efficacy of tapentadol extended-release in the treatment of cancer-related pain and improvement in the quality of life of opioid-naïve or opioid-resistant patients
Authors: Jung Ji Yoon , Chon Hong Jae , Choi Young Jin , Yeon Sang Eun , Choi Seok Young , Lee Kyung Hee 
Published: April 2022

Abstract
Purpose
This study aimed to investigate the clinical efficacy of tapentadol extended-release (ER) on pain control and the quality of life (QoL) of patients with moderate to severe chronic cancer pain in clinical practice in Korea.

Methods
In this prospective, open-label, multicenter trial, patients with sustained cancer pain as well as chronic pain, who were or were not using other analgesics were enrolled. Thirteen centers recorded a total of 752 patients during the 6-month observation period, based on the tapentadol ER dose and tolerability, prior and concomitant analgesic treatment, pain intensity, type of pain, adverse effects, and clinical global impression change (CGI-C). Of those 752 patients, 688 were enrolled, and 650 completed the study for efficacy and adverse drug reactions; among them, 349 were cancer patients.

Results
Tapentadol ER significantly reduced the mean pain intensity including neuropathic pain during the observation period by 2.9 points (from a mean 7 ± 0.87 to 4.1 ± 2.02). Furthermore, QoL was observed to be significantly improved based on the CGI-C, an objective measure.

Conclusion
This study showed that tapentadol ER was effective for treating patients with moderate to severe cancer pain and neuropathic pain, and therefore it significantly improved the patients’ QoL.
Analysis of two-decade meteorological and air quality trends in Rome (Italy)
Authors: Di Bernardino Annalisa , Iannarelli Anna Maria , Diémoz Henri , Casadio Stefano , Cacciani Marco , Siani Anna Maria 
Published: April 2022

AbstractThis study presents a trend analysis of a two-decade (2000–2020) series of surface meteorological and air quality data measured in Rome (Italy). Data series are collected at three sites in Rome downtown and its coastal surroundings. This paper fills the gap due to missing or incomplete recent information about the meteorological and atmospheric composition tendencies in the Rome area. Datasets are subjected to in-depth quality control and to statistical analysis to verify the data homogeneity, whilst trend analysis is performed using the Seasonal Kendall test. The results show a statistically significant positive trend for average air temperature (0.07 °C year−1 in urban and coastal sites), whilst maximum and minimum temperatures increase more in urban (0.10 °C year−1) than in coastal (0.01 °C year−1) environment. The water vapour mixing ratio trend is higher in the city (0.10 g kg−1 year−1) than along the coast (0.03 g kg−1 year−1). The heat index tendency is more pronounced in the Rome centre (0.11 °C year−1) than in the coast (0.06 °C year−1). The monthly cumulative precipitations do not show statistically significant trends. On the other hand, air quality generally improved: surface pollutant concentrations show a significant decrease thanks to the reduction of local emissions (C6H6, − 0.12 µg m−3 year−1; SO2, − 0.09 µg m−3 year−1; CO, − 0.02 mg m−3 year−1; NOx, − 1.28 µg m−3 year−1; NO, − 0.38 µg m−3 year−1; NO2, − 0.60 µg m−3 year−1, PM10, − 0.35 µg m−3 year−1). Only O3 shows a statistically significant positive trend (0.15 µg m−3 year−1), in agreement with wider scale studies. The outcomes suggest that whilst local and national policies contribute to the improvement of air quality, the rising of temperature—as likely consequence of climate change—may be an emerging cause of concern for human thermal discomfort and potential effect on the conservation of tangible immovable heritage.
Epilepsiechirurgie bei älteren Patienten
Authors: Hebel Jonas M. , Holtkamp Martin 
Published: April 2022

ZusammenfassungDie Entfernung des Anfallsfokus – durch Resektion oder Laserthermoablation – stellt bei ausgesuchten Patienten mit fokaler pharmakoresistenter Epilepsie eine Therapie mit guter Aussicht auf Anfallsfreiheit bei geringen Risiken dar. Die Vagusnerv- und die tiefe Hirnstimulation sind palliative Verfahren, die die Häufigkeit und die Schwere epileptischer Anfälle reduzieren sollen. Bei älteren Patienten besteht eine allgemeine Zurückhaltung hinsichtlich aller epilepsiechirurgischen Verfahren, „älter“ bedeutet in diesem Kontext in der Regel ein Lebensalter jenseits von 50 Jahren. In dieser Arbeit wird untersucht, ob es im Vergleich von älteren zu jüngeren Patienten relevante Unterschiede bezüglich Anfallsprognose und Komplikationsraten bei den verschiedenen epilepsiechirurgischen Verfahren gibt. Insgesamt ist die Datenlage dünn, es gibt kaum qualitativ hochwertige Studien. Die meisten Daten liegen für resektive Verfahren vor. Hier sind fast 700 ältere Patienten publiziert, meist in retrospektiven, monozentrischen Studien zu Temporallappenepilepsien. Zusammengefasst unterscheidet sich die Rate an Anfallsfreiheit und die an Komplikationen bei älteren Patienten nicht von der bei jüngeren Patienten. Es ist aber nicht auszuschließen, dass in der Gruppe der älteren Patienten bevorzugt besonders klare und erwartbar unkomplizierte Fälle reseziert wurden. Bei den Thermoablationsverfahren liegen keine Daten für ältere Patienten vor. Der minimal-invasive Ansatz könnte jedoch bei geringerer Komplikationsrate gerade für die Gruppe der Älteren interessant sein. Bei der Vagusnerv- und der tiefen Hirnstimulation deuten die wenigen verfügbaren Daten nicht auf Unterschiede zwischen älteren und jüngeren Patienten in Bezug auf Wirksamkeit und Sicherheit hin.
Nanotechnology-based controlled release of sustainable fertilizers. A review
Authors: Beig Bilal , Niazi Muhammad Bilal Khan , Sher Farooq , Jahan Zaib , Malik Umer Shahzad , Khan Mohammad Daud , Américo-Pinheiro Juliana Heloisa Pinê , Vo Dai-Viet N. 
Published: April 2022

AbstractThe rising population is increasing food demand, yet actual crop production is limited by the poor efficiency of classical fertilizers. In particular, only about 40–60% of fertilizer nitrogen, 15–20% of phosphorus and 50–60% of potassium are used by crop plants, the rest ending polluting the environment. Nanofertilizers are promising alternatives. Here, we review plant nutrients, synthesis of zinc oxide nanoparticles, encapsulation of nanoparticles in fertilizers, and effect on plants.
Transapical TAVI in chronic type A dissection
Authors: Mayer Christian , Zirngast Birgit , Luha Olev , Marte Wolfgang , Schmid Johannes , Toth Gabor , Nebert Clemens , Schmidt Albrecht , Mächler Heinrich 
Published: April 2022

Summary
Background
Transcatheter aortic valve implantation (TAVI) has been a routine procedure for quite some years. Advancements in technology and experience have enabled its use in even more challenging anatomies.

Case report
An 83-year-old female patient with severe aortic pathology due to chronic type A dissection after supracoronary ascending aortic repair was suffering from progressive dyspnea and recurrent cardiac decompensations due to severe aortic stenosis. She was successfully treated with a transapical TAVI procedure by our interdisciplinary heart team.

Conclusion
Transapical TAVI is a good alternative for overcoming severe aortic pathology when treating aortic stenosis.
Efficient quantile tracking using an oracle
Authors: Hammer Hugo L. , Yazidi Anis , Riegler Michael A. , Rue Håvard 
Published: April 2022

AbstractConcept drift is a well-known issue that arises when working with data streams. In this paper, we present a procedure that allows a quantile tracking procedure to cope with concept drift. We suggest using expected quantile loss, a popular loss function in quantile regression, to monitor the quantile tracking error, which, in turn, is used to efficiently adapt to concept drift. The suggested procedures adapt efficiently to concept drift, and the tracking performance is close to theoretically optimal. The procedures were further applied to three real-life streaming data sets related to Twitter event detection, activity recognition, and stock trading. The results show that the procedures are efficient at adapting to concept drift, thereby documenting the real-world applicability of the procedures. We further used asymptotic theory from statistics to show the appealing theoretical property that, if the data stream distribution is stationary over time, the procedures converge to the true quantile.
Comparison study of phase-field and level-set method for three-phase systems including two minerals
Authors: Kelm Mathis , Gärttner Stephan , Bringedal Carina , Flemisch Bernd , Knabner Peter , Ray Nadja 
Published: April 2022

AbstractWe investigate reactive flow and transport in evolving porous media. Solute species that are transported within the fluid phase are taking part in mineral precipitation and dissolution reactions for two competing mineral phases. The evolution of the three phases is not known a-priori but depends on the concentration of the dissolved solute species. To model the coupled behavior, phase-field and level-set models are formulated. These formulations are compared in three increasingly challenging setups including significant mineral overgrowth. Simulation outcomes are examined with respect to mineral volumes and surface areas as well as derived effective quantities such as diffusion and permeability tensors. In doing so, we extend the results of current benchmarks for mineral dissolution/precipitation at the pore-scale to the multiphasic solid case. Both approaches are found to be able to simulate the evolution of the three-phase system, but the phase-field model is influenced by curvature-driven motion.
Effects of 8 Weeks with Embodied Learning on 5–6-Year-Old Danish Children’s Pre-reading Skills and Word Reading Skills: the PLAYMORE Project, DK
Authors: Damsgaard Linn , Nielsen Anne-Mette Veber , Gejl Anne Kær , Malling Anne Sofie Bøgh , Jensen Søren Kildahl , Wienecke Jacob 
Published: April 2022

AbstractThe aim of this study was to investigate the effects of embodied learning on children’s pre-reading and word reading skills. We conducted a three-armed randomized controlled trial including two intervention groups and one control group. One hundred forty-nine children from grade 0 (5–6 years old) who had just started school were recruited from 10 different classes from four elementary schools. Within each class, children were randomly assigned to receive teaching of letter-sound couplings and word decoding either with whole-body movements (WM), hand movements (HM), or no movements (CON) over an 8-week period. Children were evaluated on pre-reading, word reading, and motor skills before (T1), immediately after (T2), and after 17–22 weeks of retention period (T3) following the intervention. Between-group analysis showed a significant improvement in children’s ability to name letter-sounds correctly from T1 to T2 (p < 0.001) and from T1 to T3 (p < 0.05) for WM compared to CON. HM and WM improved significantly in naming conditional letter-sounds from T1 to T2 (p < 0.01, p < 0.01) compared to CON and from T1 to T3 for the HM group compared to CON (p < 0.05). We did not find an effect on word reading or a correlation between motor skill performance and reading. Results from the present study suggest that there are beneficial effects of using whole-body movements for children. Hand motor movements indeed also had a performance effect on letter-sound knowledge; however, the whole-body movements had longer-lasting effects. We do not see an effect on whole word reading.
What happens in my code reviews? An investigation on automatically classifying review changes
Authors: Fregnan Enrico , Petrulio Fernando , Di Geronimo Linda , Bacchelli Alberto 
Published: April 2022

AbstractCode reviewing is a widespread practice used by software engineers to maintain high code quality. To date, the knowledge on the effect of code review on source code is still limited. Some studies have addressed this problem by classifying the types of changes that take place during the review process (a.k.a. review changes), as this strategy can, for example, pinpoint the immediate effect of reviews on code. Nevertheless, this classification (1) is not scalable, as it was conducted manually, and (2) was not assessed in terms of how meaningful the provided information is for practitioners. This paper aims at addressing these limitations: First, we investigate to what extent a machine learning-based technique can automatically classify review changes. Then, we evaluate the relevance of information on review change types and its potential usefulness, by conducting (1) semi-structured interviews with 12 developers and (2) a qualitative study with 17 developers, who are asked to assess reports on the review changes of their project. Key results of the study show that not only it is possible to automatically classify code review changes, but this information is also perceived by practitioners as valuable to improve the code review process. Data and materials: 10.5281/zenodo.5592254
Genome size, ploidy levels, and development of novel SSR primer to evaluate genetic diversity of Corylopsis Siebold & Zucc. germplasm collections
Authors: Lattier Jason D. , Ballard Harvey E. , Kramer Matthew , Pooler Margaret R. 
Published: April 2022

AbstractCorylopsisSeibold & Zucc. is a genus of flowering shrubs with few cultivars and little information on genome size, ploidy levels, and genetic relationships among taxa. The United States National Arboretum and collaborating gardens in North America maintain a diverse germplasm collection ofCorylopsisincluding cultivated and wild-collected taxa. The objectives of this study were to determine genome size, ploidy, and genetic diversity inCorylopsis. Flow cytometry revealed a ploidy series of diploid, tetraploid, pentaploid, and hexaploid taxa inCorylopsiswith 2C genome sizes ranging from 1.9 pg to 5.7 pg. Representative taxa were selected for root tip cytology, revealing diploid (C.platypetalaRehder & E.H. Wilson), tetraploid (C.gotoanaMakino), pentaploid (unnamed hybrid selection), and hexaploid (C.willmottiaeRehder & E.H. Wilson) taxa. Seventeen genomic simple sequence repeat markers were developed and used to determine the genetic diversity ofCorylopsis. These markers had an average of 7.4 alleles per locus with a range of three to 17 alleles. A dendrogram was generated by unweighted pair group method with arithmetic mean (UPGMA) cluster analysis using the Jaccard similarity coefficient to visualize genetic relationships and ploidy series within taxa. Information gained from this study will further breeding efforts and aid management of germplasm collections ofCorylopsis.
SARS-CoV-2 Vaccine Responses in Individuals with Antibody Deficiency: Findings from the COV-AD Study
Authors: Shields Adrian M. , Faustini Sian E. , Hill Harriet J. , Al-Taei Saly , Tanner Chloe , Ashford Fiona , Workman Sarita , Moreira Fernando , Verma Nisha , Wagg Hollie , Heritage Gail , Campton Naomi , Stamataki Zania , Klenerman Paul , Thaventhiran James E. D. , Goddard Sarah , Johnston Sarah , Huissoon Aarnoud , Bethune Claire , Elcombe Suzanne , Lowe David M. , Patel Smita Y. , Savic Sinisa , Burns Siobhan O. , Richter Alex G. ,   on behalf of the COV-AD consortium, Ahmed Zahra , Bancroft Hollie , Bates Michelle , Clifford Hayley , Davis Georgina , Dasgin Joanne , Dinally Mohammad , Dhalla Fatima , Efstathiou Elena , Elkhalifa Shuayb , Gompels Mark , Hartland Dan , Hoque Madeeha , Heritage Emily , Hughes Deborah , Ivory Ann , Jain Rashmi , Kelly Sinead , McCarthy Theresa , McGee Christopher , Mullan Daniel , Morsi Hadeil , O’Grady Eileen , Page Shannon , Peters Nicholas , Plant Timothy , Shajidevadas Archana , Slowinsksa Malgorzata , Suleiman Zehra , Townsend Neil , Trinham Charlotte , Wareham Stuart , Walder Sinead 
Published: April 2022

Abstract
Background
Vaccination prevents severe morbidity and mortality from COVID-19 in the general population. The immunogenicity and efficacy of SARS-CoV-2 vaccines in patients with antibody deficiency is poorly understood.

Objectives
COVID-19 in patients with antibody deficiency (COV-AD) is a multi-site UK study that aims to determine the immune response to SARS-CoV-2 infection and vaccination in patients with primary or secondary antibody deficiency, a population that suffers from severe and recurrent infection and does not respond well to vaccination.

Methods
Individuals on immunoglobulin replacement therapy or with an IgG less than 4 g/L receiving antibiotic prophylaxis were recruited from April 2021. Serological and cellular responses were determined using ELISA, live-virus neutralisation and interferon gamma release assays. SARS-CoV-2 infection and clearance were determined by PCR from serial nasopharyngeal swabs.

Results
A total of 5.6% (n = 320) of the cohort reported prior SARS-CoV-2 infection, but only 0.3% remained PCR positive on study entry. Seropositivity, following two doses of SARS-CoV-2 vaccination, was 54.8% (n = 168) compared with 100% of healthy controls (n = 205). The magnitude of the antibody response and its neutralising capacity were both significantly reduced compared to controls. Participants vaccinated with the Pfizer/BioNTech vaccine were more likely to be seropositive (65.7% vs. 48.0%, p = 0.03) and have higher antibody levels compared with the AstraZeneca vaccine (IgGAM ratio 3.73 vs. 2.39, p = 0.0003). T cell responses post vaccination was demonstrable in 46.2% of participants and were associated with better antibody responses but there was no difference between the two vaccines. Eleven vaccine-breakthrough infections have occurred to date, 10 of them in recipients of the AstraZeneca vaccine.

Conclusion
SARS-CoV-2 vaccines demonstrate reduced immunogenicity in patients with antibody deficiency with evidence of vaccine breakthrough infection.
Automated deep learning approach for classification of malignant melanoma and benign skin lesions
Authors: Salma Wessam , Eltrass Ahmed S. 
Published: April 2022

AbstractSkin cancer becomes a significant health problem worldwide with an increasing incidence over the past decades. Due to the fine-grained differences in the appearance of skin lesions, it is very challenging to develop an automated system for benign-malignant classification through images. This paper proposes a novel automated Computer Aided Diagnosis (CAD) system for skin lesion classification with high classification performance using accuracy low computational complexity. A pre-processing step based on morphological filtering is employed for hair removal and artifacts removal. Skin lesions are segmented automatically using Grab-cut with minimal human interaction in HSV color space. Image processing techniques are investigated for an automatic implementation of the ABCD (asymmetry, border irregularity, color and dermoscopic patterns) rule to separate malignant melanoma from benign lesions. To classify skin lesions into benign or malignant, different pretrained convolutional neural networks (CNNs), including VGG-16, ResNet50, ResNetX, InceptionV3, and MobileNet are examined. The average 5-fold cross validation results show that ResNet50 architecture combined with Support Vector Machine (SVM) achieve the best performance. The results also show the effectiveness of data augmentation in both training and testing with achieving better performance than obtaining new images. The proposed diagnosis framework is applied to real clinical skin lesions, and the experimental results reveal the superior performance of the proposed framework over other recent techniques in terms of area under the ROC curve 99.52%, accuracy 99.87%, sensitivity 98.87%, precision 98.77%, F1-score 97.83%, and consumed time 3.2 s. This reveals that the proposed framework can be utilized to help medical practitioners in classifying different skin lesions.