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Figure 1. (a) Part of the acrylic structure where the patient is enclosed to avoid external stimulus; (b) Chin rest, corresponding proportions and measurements.-Design of a Novel Servo-motorized Laser Device for Visual Pathways Diseases Therapy

The device consists mainly of an acrylic semi-spherical structure (Figure 1(a)) where visual stimuli will be shown, according to a pre-designed therapy. Four servomotors will drive the lasers, two inside the structure (short distances drive the lasers, two inside the structure (short distance therapies) and two outside (middle-long distance therapies). A chin-rest must be used to have a better line of sight fixation. A webcam with infrared light will catch the Purkinje-Sanson images to identify the sight line (Borah, 2006; Halswanter, 2011; Pambakian et al., 2000). LabVIEW software is used to control the device, including an audio stimulus along with an image-processing pipeline. Finally a microcontroller is used to control the servo movements, laser beams and buzzers.

The Brain and Propranolol Pharmacokinetics in the Elderly-Figure 1.(a)Results of the Monte-Carlo simulations to describe pharmacokinetics of young patients with validation from the Taegtmeyer 2014 publication(Taegtmeyer et al., 2014)

Propranolol has been found to be therapeutically effective, to obtain a clinical response by beta-adrenoceptor blockade, at plasma levels of greater than 20 ng/mL(Coltart et al., 1971; Frishman, 1988; Johnsson and Regàrdh, 1976). Thus, to display the data, we used highlighted plasma concentration where the pharmacokinetic curve falls below 20ng/mL threshold for therapeutic efficacy in the patient’s plasma.

Figure 2.(a)Results of the Monte-Carlo simulations describing a population of elderly patients after a single oral dose of propranolol.-The Brain and Propranolol Pharmacokinetics in the Elderly

In effort to identify the recommended Propranolol dosage for elderly patients, we identified the patient package inserts from the Food and Drug Administration (FDA) Inderal label, who manufacture propranolol. Based from FDA Wyeth Propranolol label, for dosing in the geriatric population,the label states that there were not sufficient numbers of clinical study participants who were 65-years and older to properly determine the difference in response young and elderly patients.

Figure 5.(a)Linear (y=0.45x + 57.74) dose-response relationship between plasma propranolol to % β- adrenergeric blockade derived from healthy study participants and translate into patients with angina pectoris. This image has been adapted from(Pine et al., 1975).-The Brain and Propranolol Pharmacokinetics in the Elderly

Apharmacodynamic model,with parameters in the table below, may be used to visualize the propranolol concentration-effect (β-blockade) relationship in patients suffering from angina pectoris. These results have been adapted from the Pine et al article published in Circulation in 1975 which identified a linear relationship plasma Propranolol (ng/mL) to an effect of % β-Adrenergic Blockade in a single-oral dose of 40mg Propranolol in exercising individuals (Pine et al., 1975).

opencc-by-4.0Jan 2018View details →

Figure 4. Simulation (Monte-Carlo, n=200) results elderly patients taking a 10mg oral dose resulting in similar Cmax, maximum plasma concentration, to the young patients taking a 40mg oral dose. The dotted lines illustrate the 10th and 90th percentiles of plasma levels of the elderly population with a 10mg oral administration of propranolol.-The Brain and Propranolol Pharmacokinetics in the Elderly

Thus, the package insert (see 1) recommends clinicians start at the lower end of the dosing range, without further details. Similarly, Pfizer manufactures Inderal® LA (Propranolol HCI), which is the long-acting form of propranolol and their package insert (see 2) states, “There is no information available for elderly patients.” Though the kinetics for the long-acting formdiffers from the standard form, manufactured by Wyeth, we would suspect a 10mg dose for the elderly would achieve a similar maximum plasma concentration (Cmax) to that of the younger patient cohort.This 10mg, which is 25% of the original 40mg, dosing schedule is based on our simulations at 10mg in the geriatric population.

Figure 3. Logoped 1.0 program-Modern Tools in Patient-Centred Speech Therapy for Romanian Language

The program was designed for the therapy of logoneurosis, while being equally useful for the therapeutic activities used in the treatment of dyslexic-dysgraphic disorders. Logoped 1.0 provides a vast lexical material, which is organised into several sections: exercises involving reading the syllables and the words, sentences reading, followed by phrase and text reading. The colourful design of the words and sentences, the attractive way in which they are displayed on the monitor, and the fact that it allows choosing the exercises level of difficulty render the reading activity much more attractive for the pupil (Tobolcea, 2001). Its functional schema is presented in figure 3.

Figure 4. The relationship between the functional blocks of the systemModern Tools in Patient-Centred Speech Therapy for Romanian Language

The project’s complexity results from the considerable number of research fields it presupposes: artificial intelligence (pattern recognition, learning expert systems), virtual reality, digital signal processing, digital electronic (VLSI), computer architecture, and psychology (assessment procedures and techniques, therapeutic instructions, validation experimental design). In order to assure an assisted therapy one considers the relationships between six functional blocks: patient, speech therapist, office monitor program, expert system, 3D model and patient monitor program. The information flow of the system is given in Figure 4. There is a close connection between the child, as a patient, and his speech therapist. All the other modules are designed so as to contribute to the therapeutic action of the teacher. The monitor program allows realising a complex assessment and collecting information about the child; equally, it provides the opportunity to periodically track the child’s therapy results. The child is provided instant audio feedback which allows him/her to check the audio recordings history. The home monitor program is designed so as to build a virtual interface between teacher and child in order to allow the patient to continue his therapy at home. This component is designed both for the personal computer, which is placed in the therapist’s office, and personal digital assistant (PDA) which is used at home for independent work.

Figure 9. A model that helps the diagnosis prediction-Modern Tools in Patient-Centred Speech Therapy for Romanian Language

We have already implemented many modules of Logo-DM, such as: data cleaning module, data transformation module, feature extraction module, data clustering module and a classification module for diagnosis prediction.  Figure 9 shows the model achieved using a decision tree built on complex examination data that aims to predict the patient’s diagnosis. Currently, we are testing the built models on new cases in order to estimate their quality.

Figure 8. The end-to-end operations in Logo-DM-Modern Tools in Patient-Centred Speech Therapy for Romanian Language

The useful data mining tasks for speech therapy fall into three categories: classification, clustering, and association rules. Classification places children with different speech impairments in predefined classes, and makes possible to track the characteristics of various groups. To model different classes we use many predictor variables (e.g. personal or familial anamnesis data or related to lifestyle). By clustering we group people with speech disorders on the basis of similarity of different features. This helps therapists to understand their patients. Clustering aims to find subsets of a predetermined segment, with homogeneous behavior towards various methods of therapy that can be effectively targeted by a specific therapy, but it is not based on the previous definition of groups (Danubianu, Tobolcea, & Pentiuc, 2009). Association rules aim to find out relationships between different data which seem to have no semantic dependence. The built patterns might be very useful to determine why a specific therapy program has been successful on a segment of patients with speech disorders, and on the other was ineffective. The Logo-DM system was designed to help the speech therapists to optimize the personalized therapy of dyslalia. To understand what kind of knowledge we could discover in TERAPERS’ dataset to improve speech therapy, we have to describe the collected data.

Figure .5 Architecture of the Terapers system-Modern Tools in Patient-Centred Speech Therapy for Romanian Language

Shown in Figure 5, the architecture of the Terapers system implies the existence of two main connected components: on the one hand, an intelligent system which is installed on the office computer of each speech therapist and, on the other, a mobile system which is used as a virtual friend in the therapy applied to the child (Danubianu et al., 2008). The intelligent system – which represents the fixed component of the system – is installed on each computer from the office of the speech therapist; it is made up of the following parts: • an information management module for children; • an expert system, able to produce inferences based on the data given by the assessment module; • a mouth virtual module which allows the display of all hidden movements that are likely to occur during speech; • a management module of the exercises uses, which allows creating or modifying the exercises, depending on the various therapy stages, as well as their organization into complex issues.

opencc-by-4.0Sep 2018View details →

Datasets of Vascular Networks Extracted from Retinal Images of Hypertensive Retinopathy and Glaucoma Patients

This dataset contains high resolution images of blood vessels extracted  from Digital Retinal Images for Optic Nerve Segmentation Database (DRIONS-DB). It contains 110 blood vessels of individuals of which 23.1% are patients with chronic glaucoma while the remaining 76.9% are hypertensive retinopathy patients.

opencc-by-4.0Sep 2018View details →

High Resolution Retinal Blood Vessels Datasets of Diabetic Retinopathy Patients

This dataset contains 89 high resolution image files of blood vessels extracted from publicly available retina images available in DIARETDB1

opencc-by-4.0Oct 2018View details →

Supplementary data to: Detection of Neoantigen-specific T Cells Following a Personalized Vaccine in a Patient with Glioblastoma

Supplemental Data for the patient described in the manuscript: "Detection of Neoantigen-specific T Cells Following a Personalized Vaccine in a Patient with Glioblastoma". Summary of somatic variant calls from DNA whole exome, gene FPKM from RNA sequencing, and neoantigen predictions for high-affinity (ic50 <500 nM) candidates.

opencc-by-4.0Aug 2017View details →

Multimodal optical measurement for study of lower limb tissue viability in patients with diabetes mellitus

According to the International Diabetes Federation, the challenges of early stage diagnosis and treatment effectiveness monitoring in diabetes is currently one of the highest priorities in modern healthcare. In this experimental study, the potential of combined measurements of skin fluorescence and blood perfusion by the laser Doppler flowmetry method in diagnostics of low limb diabetes complications was evaluated. With the use of Monte Carlo probabilistic modelling, the diagnostic volume and depth of the diagnosis were evaluated. The experimental study involved 76 patients with type 2 diabetes mellitus. These patients were divided into two groups depending on the degree of complications. The control group consisted of 48 healthy volunteers. The local thermal stimulation was selected as a stimulus on the blood microcirculation system. Experimental studies have shown that diabetic patients have elevated values of normalised fluorescence amplitudes, as well as a lower perfusion response to local heating. In the group of people with diabetes with trophic ulcers, these parameters also significantly differ from the control and diabetes only groups. Thus, the intensity of skin fluorescence and level of tissue blood perfusion can act as markers for various degrees of complications from the beginning of diabetes to the formation of trophic ulcers.

opencc-by-4.0Jan 2019View details →

Outcome of Childhood Adrenocortical Carcinoma in Developing Countries. Supplementary Table 1: Patients' characteristics and endocrinal manifestations

Outcome of Childhood Adrenocortical Carcinoma in Developing Countries. Supplementary Table 1: Patients’ characteristics and endocrinal manifestations

opencc-by-4.0Feb 2019View details →

netDx: Interpretable patient classification using integrated patient similarity networks

Docker image containing installed netDx software in Ubuntu to reproduce examples from the published manuscript. The R implementation of netDx is hosted at: https://github.com/BaderLab/netDx --- Publication abstract: Patient classification has widespread biomedical and clinical applications, including diagnosis, prognosis and treatment response prediction. A clinically useful prediction algorithm should be accurate, generalizable, be able to integrate diverse data types, and handle sparse data. A clinical predictor based on genomic data needs to be easily interpretable to drive hypothesis-driven research into new treatments. We describe netDx, a novel supervised patient classification framework based on patient similarity networks. netDx meets the above criteria and particularly excels at data integration and model interpretability. We compared classification performance of this method against other machine-learning algorithms, using a cancer survival benchmark with four cancer types, each requiring integration of up to six genomic and clinical data types. In these tests, netDx has significantly higher average performance than most other machine-learning approaches across most cancer types. In comparison to traditional machine learning-based patient classifiers, netDx results are more interpretable, visualizing the decision boundary in the context of patient similarity space. When patient similarity is defined by pathway-level gene expression, netDx identifies biological pathways important for outcome prediction, as demonstrated in diverse data sets of breast cancer and asthma. Thus, netDx can serve both as a patient classifier and as a tool for discovery of biological features characteristic of disease. We provide a freely available software implementation of netDx along with sample files and automation workflows in R.

opencc-by-4.0May 2019View details →

Sempa et al. 2019 - A Retrospective audit of treatment outcomes, side-effect profiles and default and mortality rates of HIV/AIDS patients at the antiretroviral clinic at Pretoria Academic Hospital.

The comprehensive demographic and long-term treatment data of the first, consecutive, 963 patients older than 18 years of age who presented for ART at the Tshwane District Hospital in Gauteng, South Africa during 2004 and 2005 were selected for analysis. All patients started ART after 2004 as part of the South African national HIV treatment plan and were treated according to the National Department of Health HIV guidelines (2004) operative at the time, i.e. eligibility for ART was CD4 <200 cells/µL or WHO stage 4 disease regardless of CD4 count. Treatment was initiated using a standardized triple-drug regimen consisting of two nucleoside reverse transcriptase inhibitors, mostly d4T and 3TC, and one non-nucleoside reverse transcriptase inhibitor, either NVP or EFV. CD4 and HIV-1 VL monitoring was performed at treatment initiation ‘baseline’ and then 6-monthly, according to the national protocol. Demographic, anthropometric, clinical, ART and 5-year longitudinal treatment response data were collected. Excluded all second-line ART visits for all patients who were switched to second-line therapy.

opencc-by-4.0May 2019View details →

Mobile Device Voice Recordings at King's College London (MDVR-KCL) from both early and advanced Parkinson's disease patients and healthy controls

Dataset description The dataset description will start with describing the local conditions and other metadata, then will continue with describing the recording procedure and annotation methodology. Finally, a brief description of the dataset deployment and publication will be given. Meta Information The dataset was recorded at King's College London (KCL) Hospital, Denmark Hill, Brixton, London SE5 9RS in the period from 26 to 29 September 2017. We used a typical examination room with about ten square meters area and a typical reverberation tome of approx. 500ms to perform the voice recordings. Due to the fact, that the voice recordings are performed in the realistic situation of doing a phone call (i.e. participant holds the phone to the preferred ear and microphone is in direct proximity to the mouth), one can assume that all recordings were performed within the reverberation radius and thus can be considered as “clean”. Recording Procedure We used a Motorola Moto G4 Smartphone as recording device. To perform the voice recordings on the device, we developed a “Toggle Recording App”, which uses the same functionalities as the voice recording module used within the i-PROGNOSIS Smartphone application, but deployed as a standalone android application. This means, that the voice capturing service runs as a standalone background service on the recording device and triggers voice recordings via on- and off-hook signals of the Smartphone. Due to the fact, that we directly record the microphone signal, and not the GSM (“Global System for Mobile Communications”) compressed stream, we end up with high quality recordings with a sample rate of 44.1 kHz and a bit depth of 16 Bit (audio CD quality). The raw, uncompressed data is directly written to the external storage of the Smartphone (SD-card) using the well-known WAVE file format (.wav). We used the following workflow to perform a voice recording: <ul> <li>Ask the participant to relax a bit and then to make a phone call to the test executor (off-hook signal triggered).}</li> <li>Ask the participant to read out “The North Wind and the Sun”</li> <li>Depending on the constitution of the participant either ask to read out “Tech. Engin. Computer applications in geography snippet”</li> <li>Start a spontaneous dialog with the participant, the test executor starts asking random questions about places of interest, local traffic, or personal interests if acceptable.</li> <li>Test executor ends call by farewell (on-hook signal triggered).</li> </ul> Annotation Scheme For each HC and PD participant, we labeled the data regarding scores on the Hoehn & Yahr (H&Y), as well as the UPDRS II part 5 and UPDRS III part 18 scale. The voice recordings are labeled in the following scheme: SI_ HS_ HYR_ UPDRS II-5_UPDRS III-18 with <ul> <li>SI as subject identification in the form IDNN, N in [0, 9]</li> <li>HS as the health status label (hc or pd accordingly)</li> <li>HYR as the expert assessed H&Y scale rating</li> <li>UPDRS II-5 as the according expert peer-reviewed score</li> <li>UPDRS III-18 as the according expert assessed score</li> </ul> For example, an audio recording with the file name “ID02_pd_1_2_1.wav” represents a recording of the third participant (First participant was anonymized as ID00), which has PD and a H&Y rating of 1, a UPDRS II-5 score of 2 and a UPDRS III-18 score of 1. At this point, it should be noted, that also all healthy controls were evaluated with regard to the introduced scales, because Parkinson's disease and voice degradation correlate, but don't match exactly. This means, that the data set includes one HC participant (ID31) with UPDRS II-5 and III-18 rating of 1, and also includes PD patients with UPDRS II-5 and III-18 ratings of 0. It should be emphasized, that this does not mean the data set includes ambiguous information, but that an expert was not able to hear voice degradation that would end up in a UPDRS rating greater than zero. Machine learning approaches may be able to nevertheless classify correctly, or at least learn to correlate, but not match PD and voice degradation at any time. Appendix North Wind and the Sun (Orthographic Version): “The North Wind and the Sun were disputing which was the stronger, when a traveler came along wrapped in a warm cloak. They agreed that the one who first succeeded in making the traveler take his cloak off should be considered stronger than the other. Then the North Wind blew as hard as he could, but the more he blew the more closely did the traveler fold his cloak around him; and at last the North Wind gave up the attempt. Then the Sun shone out warmly, and immediately the traveler took off his cloak. And so the North Wind was obliged to confess that the Sun was the stronger of the two.” BNC – Tech. Engin. Computer applications in geography snippet: “[...] This is because there is less scattering of blue light as the atmospheric path length and consequently the degree of scattering of the incoming radiation is reduced. For the same reason, the sun appears to be whiter and less orange-coloured as the observer's altitude increases; this is because a greater proportion of the sunlight comes directly to the observer's eye. Figure 5.7 is a schematic representation of the path of electromagnetic energy in the visible spectrum as it travels from the sun to the Earth and back again towards a sensor mounted on an orbiting satellite. The paths of waves representing energy prone to scattering (that is, the shorter wavelengths) as it travels from sun to Earth are shown. To the sensor it appears that all the energy has been reflected from point P on the ground whereas, in fact, it has not, because some has been scattered within the atmosphere and has never reached the ground at all. [...]”

opencc-by-sa-4.0Jan 2019View details →

Patients data for meta-analysis of genotype-phenotype associations in Bardet-Biedl Syndrome

Data used for metaanalysis of the genotype-phenotype relationship in Bardet Biedl Syndrome. File "EV table 1 literature.xlsx" describes studies that were included in the metaanalysis. File "EV table 2 dataset.xlsx" contains individual patient data. Each row corresponds to a patient. If the same patient was reported in more than 1 study, their data were merged into one row. The columns are as follows: * source - a citation to the study the patient originated in * FamilyID - randomly generated ID of a family (unique over the dataset), two persons with the same FamilyID are related. * source case n. - A unique identifier of the patient within the study * gene - A gene carrying the principal BBSome related mutation * nucleotide change (allele 1,2)  - description of the mutations in DNA individual alleles of the gene, in HGVS nomenclature * protein change (allele 1,2)  - description of how the mutations in DNA change the resulting protein, in HGVS nomenclature * type of mut allele 1,2 - whether the given mutation  is considered missense (MS) or large truncation (trunc) * mut/mut - combination of mutations for both alleles * additional mutations - mutations in other BBSome-related genes. Format is "gene: DNA mutation, protein mutation" * sex - "F" or "M"  (where reported) * age group - age group (where reported) * age - age in years. Contains fractions, decimal values and "5 month" * RD, OBE, PD, CI, REP, REN, HEART, LIV, DD - presense or absence of phenotypes, if reported. RD – retinal dystrophy, OBE – obesity, PD – polydactyly, CI – cognitive impairment , REP – reproductive system anomalies, REN – renal anomalies, HRT – heart disease, LIV – liver anomalies, DD - Developmental delay. Values are "" (not reported), "0" (no phenotype), "1" (phenotype present), "1!" conflicting reports of phenotype in multiple studies (some patients were involved in multiple studies) * ethnicity - ethnicity of the patient, if reported * ethinc group - grouping of the ethnicities into 8 larger groups (see paper for details) * note - miscellanous text, in particular contains notes on patients merged from multiple studies ==== The protocol for this meta-analysis was pre-registered with PROSPERO (CRD42018096099). PubMed and Google Scholar databases were searched in May 2018 for the following keywords: [bardet-biedl syndrome AND (genotype phenotype OR cohort)]. Other suitable records were identified by snowball searching, in particular, by retrieving relevant articles from the references of the studied full-texts. In addition, all the references included in the publicly available Euro-Wabb database (<a href="https://lovd.euro-wabb.org/home.php">https://lovd.euro-wabb.org/home.php</a>) were covered. Our search was limited to the literature published in English language and covered the period from the inception of each database to the 21st of May 2018.