Machine learning of structured and unstructured healthcare data

The widespread adoption of Electronic Health Records (EHR) systems in healthcare institutions in the United States makes machine learning based on large-scale and real-world clinical data feasible and affordable. Machine learning of healthcare data, or healthcare data analytics, has achieved numerous successes in various applications. However, there are still many challenges for machine learning of healthcare data both structured and unstructured. Longitudinal structured clinical data (e.g., lab test results, diagnoses, and medications) have an enormous variety of categories, are collected at irregularly spaced visits, and are sparsely distributed. Studies on analyzing longitudinal structured EHR data for tasks such as disease prediction and visualization are still limited. For unstructured clinical notes, existing studies mostly focus on disease prediction or cohort selection. Studies on mining clinical notes with the direct purpose to reduce costs for healthcare providers or institutions are limited. To fill in these gaps, this dissertation has three research topics.The first topic is about developing state-of-the-art predictive models to detect diabetic retinopathy using longitudinal structured EHR data. Major deep-learning-based temporal models for disease prediction are studied, implemented, and evaluated. Experimental results on a large-scale dataset show that temporal deep learning models outperform non-temporal random forests models in terms of AUPRC and recall.The second topic is about clustering temporal disease networks to visualize comorbidity progression. We propose a clustering technique to outline comorbidity progression phases as well as a new disease clustering method to simplify the visualization. Two case studies on Clostridioides difficile and stroke show the methods are effective.The third topic is clinical information extraction for medical billing. We propose a framework that consists of two methods, a rule-based and a deep-learning-based, to extract patient history information directly from clinical notes to facilitate the Evaluation and Management Services (E/M) billing. Initial results of the two prototype systems on an annotated dataset are promising and direct us for potential improvements

Software comparison for clinical Named Entity Recognition (NER): A phase-1 study for developing a computer assisted medical claims billing and coding system

Claims billing and coding is non-trivial for health care providers. Accurate coding can help medical providers get reimbursements that they deserve for their professional services. Meanwhile, incorrect coding (e.g. up-coding) is considered by authorities to be one of the most important frauds with severe penalties. Therefore, accurate coding is of great importance to medical professionals. However, claims coding is challenging. Besides the knowledge of the E/M coding system, accurate coding requires an adequate depiction of patient health conditions and treatments, part of which are contained in unstructured clinical notes, e.g. discharge summaries and physician notes. We aim to develop a coding decision support system by leveraging state-of-the-art natural language processing (NLP) techniques and algorithms. The expected result of the project is to build an effective system that can extract essential information for claims coding from real clinical narratives. This phase-1 study compared five popular existing NLP software in named entity recognition based on 108 public available transcribed medical discharge summary notes from MTsamples.com. Qualitative comparison finds that CLAMP, Amazon Comprehend Medical, and cTAKES are more powerful. Quantitative analysis shows that CLAMP is more accurate and efficient than Amazon Comprehend Medical. Future work includes integrating a section segmentation tool before NER recognition as well as testing and implementation of the system in a clinical scenario.Health Systems InnovationComputer Scienc

Evaluation of the laser-induced thermotherapy treatment effect of breast cancer based on tissue viscoelastic properties

Photothermal therapy (PTT) has been emerging as an effective, minimally invasive approach to treat cancers. However, a method to quantitatively evaluate the treatment effect after laser-induced thermotherapy (LITT) is needed. In this study, we used 808 nm laser radiation with three different power densities to treat the breast cancer tissue from 4T1 cell lines in a mouse model. The viscoelastic properties of the treated cancer tissues were characterized by a two-term Prony series using a ramp-hold indentation method. We observed that instantaneous shear modulus G0 was significantly higher for the treated cancer tissues than that of the untreated tissue when treated with a power density of 1.5 W/cm2, but significantly lower with a power density of 2.5 W/cm2. The long-term shear modulus G∞ was also significantly higher for the cancer tissue at 1.5 W/cm2, compared to the untreated tissue. The treatment effects were verified by estimating the cell apoptosis rate using terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL). Our results indicate that the viscoelastic properties of the tissue could potentially be used as biomarkers for evaluating the LITT treatment effect. In addition, we also observed a strain-independent behavior of the treated cancer tissue, which provided useful information for applying in vivo imaging method such as magnetic resonance elastography (MRE) for treatment evaluation based on biomechanical properties

A Complete Genome Sequence of <i>Podosphaera xanthii</i> Isolate YZU573, the Causal Agent of Powdery Mildew Isolated from Cucumber in China

Podosphaera xanthii is a well-known obligate biotrophic pathogen that causes powdery mildew (PM) disease on cucurbitaceous plants and is one of the most important limiting factors for cucumber production worldwide. To better understand the avirulence effector proteins in this species that are known to be involved in host-pathogen interaction, the draft genome assembly of P. xanthii isolate YZU573 from cucumber leaves with symptoms of PM was obtained with a hybrid approach, combining nanopore long-read and llumina paired-end sequencing. The final P. xanthii YZU573 genome assembly of 152.7 Mb consists of 58 contigs, with an N50 value of 0.75 Mb and 6491 predicted protein-coding genes. The effector analysis using the whole-genome sequence information revealed a total of 87 putative effector candidates, and 65 of them had their analogs, whereas the remaining 22 were novel ones. The new P. xanthii genome provides valuable resources to better understand plant-microbe interaction in cucumber PM disease

Multi-branching Temporal Convolutional Network with Tensor Data Completion for Diabetic Retinopathy Prediction

Diabetic retinopathy (DR), caused by damage to the blood vessels in the tissue of the retina, is a  microvascular complication of diabetes. DR is the leading cause of vision loss among working-aged adults. However, due to the low compliance rate of DR screening and expensive medical devices for ophthalmic exams, many DR patients did not seek proper medical attention until DR develops to irreversible stages (i.e., vision loss). Fortunately, the widely available electronic health record (EHR) databases provide an unprecedented opportunity to develop cost-effective machine-learning tools for DR detection. This paper proposes a Multi-branching Temporal Convolutional Network with Tensor Data Completion (MB-TCN-TC) model to analyze the longitudinal EHRs collected from diabetic patients for DR prediction. Experimental results demonstrate that the proposed MB-TCN-TC model not only effectively copes with the imbalanced data and missing value issues commonly seen in EHR datasets but also captures the temporal correlation and complicated interactions among medical variables in the longitudinal clinical records, yielding superior prediction performance compared to existing methods.</p

Diverged Effects of Piperine on Testicular Development: Stimulating Leydig Cell Development but Inhibiting Spermatogenesis in Rats

Background: Piperine is the primary pungent alkaloid isolated from the fruit of black peppercorns. Piperine is used frequently in dietary supplements and traditional medicines. The objective of the present study was to investigate the effects of piperine on the testis development in the pubertal rat.Methods: Piperine (0 or 5 or 10 mg/kg) was gavaged to 35-day-old male Sprague-Dawley rats for 30 days. Serum levels of testosterone (T), luteinizing hormone (LH), and follicle-stimulating hormone (FSH) were measured. The development of adult Leydig cell population was also analyzed 65 days postpartum. For in vitro studies, immature Leydig cells were isolated from 35-day-old male rats and treated with 50 μM piperine in the presence of different steroidogenic stimulators/substrates for 24 h.Results: Thirty-day treatment of rats with piperine significantly increased serum T levels without affecting LH concentrations. However, piperine treatment reduced serum FSH levels. Consistent with increase in serum T, piperine increased Leydig cell number, cell size, and multiple steroidogenic pathway proteins, including steroidogenic acute regulatory protein, cholesterol side-chain cleavage enzyme, 3β-hydroxysteroid dehydrogenase 1, 17α-hydroxylase/20-lyase, and steroidogenic factor 1 expression levels. Piperine significantly increased the ratio of phospho-AKT1 (pAKT1)/AKT1, phosphos-AKT2 (pAKT2)/AKT2, and phospho-ERK1/2 (pERK1/2)/ERK1/2 in the testis. Interestingly, piperine inhibited spermatogenesis. Piperine in vitro also increased androgen production and stimulated cholesterol side-chain cleavage enzyme and 17α-hydroxylase/20-lyase activities in immature Leydig cells.Conclusion: Piperine stimulates pubertal Leydig cell development by increasing Leydig cell number and promoting its maturation while it inhibits spermatogenesis in the rat. ERK1/2 and AKT pathways may involve in the piperine-mediated stimulation of Leydig cell development

Effect of Backbone Regiochemistry on Conductivity, Charge Density, and Polaron Structure of n-Doped Donor-Acceptor Polymers

We investigated the influence of backbone regiochemistry on the conductivity, charge density, and polaron structure in the widely studied n-doped donor-acceptor polymer poly[N,N'-bis(2-octyldodecyl)-1,4,5,8-naphthalenediimide-2,6-diyl]-alt-5,5'-(2,2'-bithiophene) [P-(NDI2OD-T2)]. In contrast to classic semicrystalline polymers such as poly(3-hexylthiophene) (P3HT), the regioirregular (RI) structure of the naphthalenediimide (NDI)-bithiophene (T2) backbone does not alter the intramolecular steric demand of the chain versus the regioregular (RR) polymer, yielding RI-P(NDI2OD-T2) with similar energetics and optical features as its RR counterpart. By combining the electrical, UV-vis/infrared, X-ray diffraction, and electron paramagnetic resonance data and density functional theory calculations, we quantitatively characterized the conductivity, aggregation, crystallinity, and charge density, and simulated the polaron structures, molecular vibrations, and spin density distribution of RR-/RI-P(NDI2OD-T2). Importantly, we observed that RI-P(NDI2OD-T2) can be doped to a greater extent compared to its RR counterpart. This finding is remarkable and contrasts benchmark P3HT, allowing us to uniquely study the role of regiochemistry on the charge-transport properties of n-doped donor-acceptor polymers

Sequential Doping of Ladder-Type Conjugated Polymers for Thermally Stable n-Type Organic Conductors

Doping of organic semiconductors is a powerful tool to optimize the performance of various organic (opto)electronic and bioelectronic devices. Despite recent advances, the low thermal stability of the electronic properties of doped polymers still represents a significant obstacle to implementing these materials into practical applications. Hence, the development of conducting doped polymers with excellent long-term stability at elevated temperatures is highly desirable. Here, we report on the sequential doping of the ladder-type polymer poly-(benzimidazobenzophenanthroline) (BBL) with a benzimidazole-based dopant (i.e., N-DMBI). By combining electrical, UV-vis/infrared, X-ray diffraction, and electron paramagnetic resonance measurements, we quantitatively characterized the conductivity, Seebeck coefficient, spin density, and microstructure of the sequentially doped polymer films as a function of the thermal annealing temperature. Importantly, we observed that the electrical conductivity of N-DMBI-doped BBL remains unchanged even after 20 h of heating at 190 degrees C. This finding is remarkable and of particular interest for organic thermoelectrics.Funding Agencies|Swedish Research CouncilSwedish Research Council [2016-03979]; AForsk [18-313, 19310]; Olle Engkvists Stiftelse [204-0256]; Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linkoping University [2009 00971]; Finnish Cultural FoundationFinnish Cultural Foundation; Finnish Foundation for Technology Promotion; Knut and Alice Wallenberg FoundationKnut &amp; Alice Wallenberg Foundation; Knut and Alice Wallenberg FoundationKnut &amp; Alice Wallenberg Foundation [Dnr KAW 2014.0041]</p

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<p>Background: Piperine is the primary pungent alkaloid isolated from the fruit of black peppercorns. Piperine is used frequently in dietary supplements and traditional medicines. The objective of the present study was to investigate the effects of piperine on the testis development in the pubertal rat.</p><p>Methods: Piperine (0 or 5 or 10 mg/kg) was gavaged to 35-day-old male Sprague-Dawley rats for 30 days. Serum levels of testosterone (T), luteinizing hormone (LH), and follicle-stimulating hormone (FSH) were measured. The development of adult Leydig cell population was also analyzed 65 days postpartum. For in vitro studies, immature Leydig cells were isolated from 35-day-old male rats and treated with 50 μM piperine in the presence of different steroidogenic stimulators/substrates for 24 h.</p><p>Results: Thirty-day treatment of rats with piperine significantly increased serum T levels without affecting LH concentrations. However, piperine treatment reduced serum FSH levels. Consistent with increase in serum T, piperine increased Leydig cell number, cell size, and multiple steroidogenic pathway proteins, including steroidogenic acute regulatory protein, cholesterol side-chain cleavage enzyme, 3β-hydroxysteroid dehydrogenase 1, 17α-hydroxylase/20-lyase, and steroidogenic factor 1 expression levels. Piperine significantly increased the ratio of phospho-AKT1 (pAKT1)/AKT1, phosphos-AKT2 (pAKT2)/AKT2, and phospho-ERK1/2 (pERK1/2)/ERK1/2 in the testis. Interestingly, piperine inhibited spermatogenesis. Piperine in vitro also increased androgen production and stimulated cholesterol side-chain cleavage enzyme and 17α-hydroxylase/20-lyase activities in immature Leydig cells.</p><p>Conclusion: Piperine stimulates pubertal Leydig cell development by increasing Leydig cell number and promoting its maturation while it inhibits spermatogenesis in the rat. ERK1/2 and AKT pathways may involve in the piperine-mediated stimulation of Leydig cell development.</p

A Chemically Doped Naphthalenediimide-Bithiazole Polymer for n-Type Organic Thermoelectrics

The synthesis of a novel naphthalenediimide (NDI)-bithiazole (Tz2)-based polymer [P(NDI2OD-Tz2)] is reported, and structural, thin-film morphological, as well as charge transport and thermoelectric properties are compared to the parent and widely investigated NDI-bithiophene (T2) polymer [P(NDI2OD-T2)]. Since the steric repulsions in Tz2 are far lower than in T2, P(NDI2OD-Tz2) exhibits a more planar and rigid backbone, enhancing p-p chain stacking and intermolecular interactions. In addition, the electron-deficient nature of Tz2 enhances the polymer electron affinity, thus reducing the polymer donor-acceptor character. When n-doped with amines, P(NDI2OD-Tz2) achieves electrical conductivity (approximate to 0.1 S cm(-1)) and a power factor (1.5 mu W m(-1) K-2) far greater than those of P(NDI2OD-T2) (0.003 S cm(-1) and 0.012 mu W m(-1) K-2, respectively). These results demonstrate that planarized NDI-based polymers with reduced donor-acceptor character can achieve substantial electrical conductivity and thermoelectric response.Funding Agencies|Knut and Alice Wallenberg Foundation; Swedish Foundation for Strategic Research; VINNOVA [2015-04859]; Swedish Research Council [2016-03979]; Advanced Functional Materials Center at Linkoping University [2009-00971]; U.S. Department of Commerce, National Institute of Standards and Technology, Center for Hierarchical Materials Design (CHiMaD) [70NANB14H012]; DOE Office of Science [DE-AC02-06CH11357]; DFG within the CoEcfaed [KI-1094/9, FA 1502/1-1]; Humboldt Foundation</p