Estimating Blood Pressure from Photoplethysmogram Signal and Demographic Features using Machine Learning Techniques

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the Blood pressure (BP). Hypertension always leads to other health complications. Continuous monitoring of BP is very important; however, cuff-based BP measurements are discrete and uncomfortable to the user. To address this need, a cuff-less, continuous and a non-invasive BP measurement system is proposed using Photoplethysmogram (PPG) signal and demographic features using machine learning (ML) algorithms. PPG signals were acquired from 219 subjects, which undergo pre-processing and feature extraction steps. Time, frequency and time-frequency domain features were extracted from the PPG and their derivative signals. Feature selection techniques were used to reduce the computational complexity and to decrease the chance of over-fitting the ML algorithms. The features were then used to train and evaluate ML algorithms. The best regression models were selected for Systolic BP (SBP) and Diastolic BP (DBP) estimation individually. Gaussian Process Regression (GPR) along with ReliefF feature selection algorithm outperforms other algorithms in estimating SBP and DBP with a root-mean-square error (RMSE) of 6.74 and 3.59 respectively. This ML model can be implemented in hardware systems to continuously monitor BP and avoid any critical health conditions due to sudden changes.Comment: Accepted for publication in Sensor, 14 Figures, 14 Table

Transfer Learning with Deep Convolutional Neural Network (CNN) for Pneumonia Detection using Chest X-ray

Pneumonia is a life-threatening disease, which occurs in the lungs caused by either bacterial or viral infection. It can be life-endangering if not acted upon in the right time and thus an early diagnosis of pneumonia is vital. The aim of this paper is to automatically detect bacterial and viral pneumonia using digital x-ray images. It provides a detailed report on advances made in making accurate detection of pneumonia and then presents the methodology adopted by the authors. Four different pre-trained deep Convolutional Neural Network (CNN)- AlexNet, ResNet18, DenseNet201, and SqueezeNet were used for transfer learning. 5247 Bacterial, viral and normal chest x-rays images underwent preprocessing techniques and the modified images were trained for the transfer learning based classification task. In this work, the authors have reported three schemes of classifications: normal vs pneumonia, bacterial vs viral pneumonia and normal, bacterial and viral pneumonia. The classification accuracy of normal and pneumonia images, bacterial and viral pneumonia images, and normal, bacterial and viral pneumonia were 98%, 95%, and 93.3% respectively. This is the highest accuracy in any scheme than the accuracies reported in the literature. Therefore, the proposed study can be useful in faster-diagnosing pneumonia by the radiologist and can help in the fast airport screening of pneumonia patients.Comment: 13 Figures, 5 tables. arXiv admin note: text overlap with arXiv:2003.1314

Lupus cystitis presenting with urinary symptoms.

We present a case of a young woman presenting with irritative lower urinary tract symptoms and microscopic hematuria who was diagnosed with systemic lupus erythematosus (SLE). Abdominal ultrasound revealed bilateral hydronephrosis and a thickened bladder wall. Cystoscopic evaluation revealed severe diffuse inflammation, erythema and hemorrhage at the trigone with punctate extensions to the bladder base. She was treated with prednisone and mycophenolate mofetil with improvements in her symptoms and ultrasound findings. Lupus cystitis is a rare manifestation of SLE

Whole-Genome Sequencing and Concordance Between Antimicrobial Susceptibility Genotypes and Phenotypes of Bacterial Isolates Associated with Bovine Respiratory Disease.

Extended laboratory culture and antimicrobial susceptibility testing timelines hinder rapid species identification and susceptibility profiling of bacterial pathogens associated with bovine respiratory disease, the most prevalent cause of cattle mortality in the United States. Whole-genome sequencing offers a culture-independent alternative to current bacterial identification methods, but requires a library of bacterial reference genomes for comparison. To contribute new bacterial genome assemblies and evaluate genetic diversity and variation in antimicrobial resistance genotypes, whole-genome sequencing was performed on bovine respiratory disease-associated bacterial isolates (Histophilus somni, Mycoplasma bovis, Mannheimia haemolytica, and Pasteurella multocida) from dairy and beef cattle. One hundred genomically distinct assemblies were added to the NCBI database, doubling the available genomic sequences for these four species. Computer-based methods identified 11 predicted antimicrobial resistance genes in three species, with none being detected in M. bovis While computer-based analysis can identify antibiotic resistance genes within whole-genome sequences (genotype), it may not predict the actual antimicrobial resistance observed in a living organism (phenotype). Antimicrobial susceptibility testing on 64 H. somni, M. haemolytica, and P. multocida isolates had an overall concordance rate between genotype and phenotypic resistance to the associated class of antimicrobials of 72.7% (P < 0.001), showing substantial discordance. Concordance rates varied greatly among different antimicrobial, antibiotic resistance gene, and bacterial species combinations. This suggests that antimicrobial susceptibility phenotypes are needed to complement genomically predicted antibiotic resistance gene genotypes to better understand how the presence of antibiotic resistance genes within a given bacterial species could potentially impact optimal bovine respiratory disease treatment and morbidity/mortality outcomes

AXES at TRECVID 2012: KIS, INS, and MED

The AXES project participated in the interactive instance search task (INS), the known-item search task (KIS), and the multimedia event detection task (MED) for TRECVid 2012. As in our TRECVid 2011 system, we used nearly identical search systems and user interfaces for both INS and KIS. Our interactive INS and KIS systems focused this year on using classifiers trained at query time with positive examples collected from external search engines. Participants in our KIS experiments were media professionals from the BBC; our INS experiments were carried out by students and researchers at Dublin City University. We performed comparatively well in both experiments. Our best KIS run found 13 of the 25 topics, and our best INS runs outperformed all other submitted runs in terms of P@100. For MED, the system presented was based on a minimal number of low-level descriptors, which we chose to be as large as computationally feasible. These descriptors are aggregated to produce high-dimensional video-level signatures, which are used to train a set of linear classifiers. Our MED system achieved the second-best score of all submitted runs in the main track, and best score in the ad-hoc track, suggesting that a simple system based on state-of-the-art low-level descriptors can give relatively high performance. This paper describes in detail our KIS, INS, and MED systems and the results and findings of our experiments

Cumulative Burden of Morbidity Among Testicular Cancer Survivors After Standard Cisplatin-Based Chemotherapy: A Multi-Institutional Study

Purpose In this multicenter study, we evaluated the cumulative burden of morbidity (CBM) among > 1,200 testicular cancer survivors and applied factor analysis to determine the co-occurrence of adverse health outcomes (AHOs). Patients and Methods Participants were ≤ 55 years of age at diagnosis, finished first-line chemotherapy ≥ 1 year previously, completed a comprehensive questionnaire, and underwent physical examination. Treatment data were abstracted from medical records. A CBM score encompassed the number and severity of AHOs, with ordinal logistic regression used to assess associations with exposures. Nonlinear factor analysis and the nonparametric dimensionality evaluation to enumerate contributing traits procedure determined which AHOs co-occurred. Results Among 1,214 participants, approximately 20% had a high (15%) or very high/severe (4.1%) CBM score, whereas approximately 80% scored medium (30%) or low/very low (47%). Increased risks of higher scores were associated with four cycles of either ifosfamide, etoposide, and cisplatin (odds ratio [OR], 1.96; 95% CI, 1.04 to 3.71) or bleomycin, etoposide, and cisplatin (OR, 1.44; 95% CI, 1.04 to 1.98), older attained age (OR, 1.18; 95% CI, 1.10 to 1.26), current disability leave (OR, 3.53; 95% CI, 1.57 to 7.95), less than a college education (OR, 1.44; 95% CI, 1.11 to 1.87), and current or former smoking (OR, 1.28; 95% CI, 1.02 to 1.63). CBM score did not differ after either chemotherapy regimen ( P = .36). Asian race (OR, 0.41; 95% CI, 0.23 to 0.72) and vigorous exercise (OR, 0.68; 95% CI, 0.52 to 0.89) were protective. Variable clustering analyses identified six significant AHO clusters (χ2 P < .001): hearing loss/damage, tinnitus (OR, 16.3); hyperlipidemia, hypertension, diabetes (OR, 9.8); neuropathy, pain, Raynaud phenomenon (OR, 5.5); cardiovascular and related conditions (OR, 5.0); thyroid disease, erectile dysfunction (OR, 4.2); and depression/anxiety, hypogonadism (OR, 2.8). Conclusion Factors associated with higher CBM may identify testicular cancer survivors in need of closer monitoring. If confirmed, identified AHO clusters could guide the development of survivorship care strategies

Molecular testing for the clinical diagnosis of fibrolamellar carcinoma.

Fibrolamellar carcinoma has a distinctive morphology and immunophenotype, including cytokeratin 7 and CD68 co-expression. Despite the distinct findings, accurate diagnosis of fibrolamellar carcinoma continues to be a challenge. Recently, fibrolamellar carcinomas were found to harbor a characteristic somatic gene fusion, DNAJB1-PRKACA. A break-apart fluorescence in situ hybridization (FISH) assay was designed to detect this fusion event and to examine its diagnostic performance in a large, multicenter, multinational study. Cases initially classified as fibrolamellar carcinoma based on histological features were reviewed from 124 patients. Upon central review, 104 of the 124 cases were classified histologically as typical of fibrolamellar carcinoma, 12 cases as 'possible fibrolamellar carcinoma' and 8 cases as 'unlikely to be fibrolamellar carcinoma'. PRKACA FISH was positive for rearrangement in 102 of 103 (99%) typical fibrolamellar carcinomas, 9 of 12 'possible fibrolamellar carcinomas' and 0 of 8 cases 'unlikely to be fibrolamellar carcinomas'. Within the morphologically typical group of fibrolamellar carcinomas, two tumors with unusual FISH patterns were also identified. Both cases had the fusion gene DNAJB1-PRKACA, but one also had amplification of the fusion gene and one had heterozygous deletion of the normal PRKACA locus. In addition, 88 conventional hepatocellular carcinomas were evaluated with PRKACA FISH and all were negative. These findings demonstrate that FISH for the PRKACA rearrangement is a clinically useful tool to confirm the diagnosis of fibrolamellar carcinoma, with high sensitivity and specificity. A diagnosis of fibrolamellar carcinoma is more accurate when based on morphology plus confirmatory testing than when based on morphology alone

Molecular investigations in date palm genetic structure and diversity among commercially important date palm cultivars (Phoenix dactylifera L.)

2019 Fall.Includes bibliographical references.The date palm, Phoenix dactylifera L. is the notable palm which produces a nutrient-rich edible fruit (the date), well known for its unique attributes of medicine and healthy energy. It is a species that has been cultivated since early civilizations in the fertile crescent and later in the Middle East. It is typically cloned with many cultivars (over 3000). A means of accurately identifying specific clones and an understanding of the relationships among major commercial cultivars would provide valuable information for the maintenance, potentially an improvement and continued conservation of superior genotypes. Phylogenetic relationships amid commercial date cultivars are poorly understood, despite their importance. This research aimed at providing applicable knowledge through an expedient technique, by developing an exclusively tailored Simple Sequence Repeat (SSR) panel, custom-made for date palm fingerprinting and molecular identification also named as 'Dates PalmàPrinting'. This assembled modified genotyping by microsatellite markers provides a standardized approach to cultivar identification and a quality control application in date palm micropropagation production. A deeper understanding and relationship of today's major commercial cultivars is incomplete. Improving the development and productivity of this tree species is restricted due to few genetic resources. Only regionally narrowed studies have been conducted but it is more important to have a broader base of such knowledge. The present research reports on 20 selected, commercially important date palm cultivars, consisting of 18 females and 2 males, which are grown throughout the world. The knowledge of relationships among these cultivars is needed, although the date palm genome has been mostly sequenced (90.2 %) with 41,660 gene models representing an 82,354 scaffold. The relationships among the major cultivars remain unclear. Presently, the information on the characterization of these cultivars requires an assessment to better understand the relationships among the superior genotypes. The use of microsatellites, due to their accuracy and high polymorphic capability, have led to fine scaled phylogenies. The phylogenetic relationships were determined using neighbor joining un-rooted trees correlated with genetic structure clustering. Primer selections were achieved from evaluation of 14 nuclear SSR loci isolated from P. dactylifera. Results revealed a high degree of polymorphism observed in the 20 cultivars with fewer common alleles than anticipated. Within the cultivars studied, a broad heterozygosity across base pair (bp) amplification data has led to an understanding of limited inbreeding, accounting for possible adaptation to environmental changes and revealing conserved extensive array of genomic structure. Population structure analysis suggests a large genetic boundary between Northwest African and Middle Eastern cultivars with 6 subpopulations that represent divergences and fragments of admixture in cultivars present in these regions. The possible selection of potential and good quality parents is achievable for improving cultivars by generating population and structure maps. This analysis documents patterns of relationship and provides genetic structure and diversity of gene pool specificity complexes of date palm cultivars. This study provides insights about the relationships that exist among cultivars of interest through genetic sequence analysis using SSRs, facilitating the development of a standard approach to identification and enhancements to the micropropagation process. Keywords: Microsatellites, Phoenix dactylifera L., Simple sequence repeats, Phylogenetics, Genetic structure, Date palm, Genetic diversit