Daily estimates of individual discharge likelihood with deep learning natural language processing in general medicine: a prospective and external validation study.

Machine learning, in particular deep learning, may be able to assist in the prediction of the length of stay and timing of discharge for individual patients. Artificial neural networks applied to medical text have previously shown promise in this area. In this study, a previously derived artificial neural network was applied to prospective and external validation datasets. In the prediction of discharge within the next 2 days, when the algorithm was applied to prospective and external datasets, the area under the receiver operator curve for this task were 0.78 and 0.74, respectively. The performance in the prediction of discharge within the next 7 days was more limited (area under the receiver operator curve 0.68 and 0.67). This study has shown that in prospective and external validation datasets the previously derived deep learning algorithms have demonstrated moderate performance in the prediction of which patients will be discharged within the next 2 days. Future studies may seek to further refine or evaluate the effect of the implementation of such algorithms.

Mixed-data deep learning in repeated predictions of general medicine length of stay: a derivation study.

The accurate prediction of likely discharges and estimates of length of stay (LOS) aid in effective hospital administration and help to prevent access block. Machine learning (ML) may be able to help with these tasks. For consecutive patients admitted under General Medicine at the Royal Adelaide Hospital over an 8-month period, daily ward round notes and relevant discrete data fields were collected from the electronic medical record. These data were then split into training and testing sets (7-month/1-month train/test split) prior to use in ML analyses aiming to predict discharge within the next 2 days, discharge within the next 7 days and an estimated date of discharge (EDD). Artificial neural networks and logistic regression were effective at predicting discharge within 48 h of a given ward round note. These models achieved an area under the receiver operator curve (AUC) of 0.80 and 0.78, respectively. Prediction of discharge within 7 days of a given note was less accurate, with artificial neural network returning an AUC of 0.68 and logistic regression an AUC of 0.61. The generation of an exact EDD remains inaccurate. This study has shown that repeated estimates of LOS using daily ward round notes and mixed-data inputs are effective in the prediction of general medicine discharges in the next 48 h. Further research may seek to prospectively and externally validate models for prediction of upcoming discharge, as well as combination human-ML approaches for generating EDDs.

Spatial Control of the Self-assembled Block Copolymer Domain Orientation and Alignment on Photopatterned Surfaces.

Polarity-switching photopatternable guidelines can be directly used to both orient and direct the self-assembly of block copolymers. We report the orientation and alignment of poly(styrene-block-4-trimethylsilylstyrene) (PS-b-PTMSS) with a domain periodicity, L0, of 44 nm on thin photopatternable grafting surface treatments (pGSTs) and cross-linkable surface treatments (pXSTs), containing acid-labile 4-tert-butoxystyrene monomer units. The surface treatment was exposed using electron beam lithography to create well-defined linear arrays of neutral and preferential regions. Directed self-assembly (DSA) of PS-b-PTMSS with much lower defectivity was observed on pXST than on pGST guidelines. The study of the effect of film thickness on photoacid diffusion by Fourier transform infrared spectroscopy and near-edge X-ray absorption fine structure spectroscopy suggested slower diffusion in thinner films, potentially enabling production of guidelines with sharper interfaces between the unexposed and exposed lines, and thus, the DSA of PS-b-PTMSS on thinner pXST guidelines resulted in better alignment control.

Prediction of general medical admission length of stay with natural language processing and deep learning: a pilot study.

Length of stay (LOS) and discharge destination predictions are key parts of the discharge planning process for general medical hospital inpatients. It is possible that machine learning, using natural language processing, may be able to assist with accurate LOS and discharge destination prediction for this patient group. Emergency department triage and doctor notes were retrospectively collected on consecutive general medical and acute medical unit admissions to a single tertiary hospital from a 2-month period in 2019. These data were used to assess the feasibility of predicting LOS and discharge destination using natural language processing and a variety of machine learning models. 313 patients were included in the study. The artificial neural network achieved the highest accuracy on the primary outcome of predicting whether a patient would remain in hospital for > 2 days (accuracy 0.82, area under the received operator curve 0.75, sensitivity 0.47 and specificity 0.97). When predicting LOS as an exact number of days, the artificial neural network achieved a mean absolute error of 2.9 and a mean squared error of 16.8 on the test set. For the prediction of home as a discharge destination (vs any non-home alternative), all models performed similarly with an accuracy of approximately 0.74. This study supports the feasibility of using natural language processing to predict general medical inpatient LOS and discharge destination. Further research is indicated with larger, more detailed, datasets from multiple centres to optimise and examine the accuracy that may be achieved with such predictions.

Depression and anxiety among HIV-positive men who have sex with men and men who have sex with women in China.

China is experiencing an emerging HIV epidemic among men who have sex with men (MSM). Minority stress theory posits that marginalized populations experience additional stress, which influences experiences of psychological distress and health outcomes. This study aimed to understand psychological distress of MSM relative to men who have sex with women (MSW) in an urban Chinese setting. Cross-sectional survey data were collected from 162 HIV-positive Chinese men receiving HIV treatment at Beijing's Ditan Hospital. Multiple linear regression with imputation was used to identify correlates of psychological distress. Relative to MSW, MSM were younger, more educated, and less likely to be in a relationship or have children. While both groups reported clinically elevated levels of depression and anxiety, sexual behavior was not associated with either outcome. Higher endorsement of depression symptomology was associated with worse reported physical health (ß = -1.37, p < .05) and greater endorsement of maladaptive coping (ß = 2.39, p < .05), whereas higher endorsement of anxiety symptomology was associated with greater endorsement of adaptive coping (ß = 0.78, p < .05), diminished physical health (ß = -0.86, p < .05), and a high school or greater level of education (ß = 4.13, p < .05). These findings suggest that interventions targeting coping strategies may address psychological distress among HIV-positive Chinese men.

Orientation Control of Block Copolymers Using Surface Active, Phase-Preferential Additives.

Orientation control of thin film nanostructures derived from block copolymers (BCPs) are of great interest for various emerging technologies like separation membranes, nanopatterning, and energy storage. While many BCP compositions have been developed for these applications, perpendicular orientation of these BCP domains is still very challenging to achieve. Herein we report on a new, integration-friendly approach in which small amounts of a phase-preferential, surface active polymer (SAP) was used as an additive to a polycarbonate-containing BCP formulation to obtain perpendicularly oriented domains with 19 nm natural periodicity upon thermal annealing. In this work, the vertically oriented BCP domains were used to demonstrate next generation patterning applications for advanced semiconductor nodes. Furthermore, these domains were used to demonstrate pattern transfer into a hardmask layer via commonly used etch techniques and graphoepitaxy-based directed self-assembly using existing lithographic integration schemes. We believe that this novel formulation-based approach can easily be extended to other applications beyond nanopatterning.

Testing the feasibility and acceptability of a chaplaincy intervention to improving treatment attitudes and self-efficacy of adolescents with cystic fibrosis: a pilot study.

Religious factors are known to contribute to treatment adherence in different patient populations, and religious coping has been found to be particularly important to adolescents dealing with chronic diseases. Adherence to prescribed treatments slows disease progression and contributes to desirable outcomes in most patients, and, therefore, adherence-promoting interventions provided by chaplains could be beneficial to various patient populations. The current article describes a pilot study to test the feasibility of a theoretically and empirically based chaplain intervention to promote treatment adherence for adolescents with CF. Cognitive interviews were conducted 24 with adolescents with CF, and content analysis was used to identify themes, which informed revision of the intervention protocol. The authors thought that presenting the methods and results of this pilot study would be helpful for chaplains who want to conduct intervention research. The results indicated that the proposed intervention was acceptable and feasible to deliver in hard copy or an electronic platform.

Directed self-assembly of silicon-containing block copolymer thin films.

The directed self-assembly (DSA) of lamella-forming poly(styrene-block-trimethylsilylstyrene) (PS-PTMSS, L0=22 nm) was achieved using a combination of tailored top interfaces and lithographically defined patterned substrates. Chemo- and grapho-epitaxy, using hydrogen silsesquioxane (HSQ) based prepatterns, achieved density multiplications up to 6× and trench space subdivisions up to 7×, respectively. These results establish the compatibility of DSA techniques with a high etch contrast, Si-containing BCP that requires a top coat neutral layer to enable orientation.

"A remarkable experience of god, shaping us as a family": parents' use of faith following child's rare disease diagnosis.

A child's chronic illness can lead parents to utilize different types of coping, including religious beliefs and practices. Previous studies have generally focused on life-shortening diagnoses. The present study explored parental use of faith when the diagnosis was not life-shortening, using grounded-theory qualitative methodology. Data were collected using semi-structured telephone interviews with N = 12 parents of children diagnosed with Neuroendocrine Hyperplasia of Infancy (NEHI); approximately 50% of the diagnosed population in the United States at the time of the interview. Participants used faith to cope and make meaning in five ways: parents believed NEHI happened for a reason; beliefs provided resilience; parents were sustained by faith communities; beliefs affected parents' behavior; and beliefs developed over time. The results suggest that chaplains develop means for universal screening for spiritual struggle; educating congregational clergy how to support families in which a child has a chronic illness; and assisting parents construct meaning of their experience.

Factor analyses of a social support scale using two methods.

PURPOSE: Evaluation and comparison of the factor structure of the Medical Outcomes Study Social Support Survey (MOS-SSS) using both confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) with two samples of people living with HIV/AIDS in China. METHODS: Secondary analyses were conducted with data from two comparable samples of 320 people living with HIV/AIDS from the same hospital using the same inclusion criteria. The first sample of 120 was collected in 2006, and the second sample of 200 was collected in 2012. For each sample, CFA was first performed on the original four-factor structure to check model fit, followed by EFA to explore other factor structures and a subsequent CFA for model fit statistics to be compared to the original four-factor CFA. RESULTS: In both samples, CFA on the originally hypothesized four-factor structure yielded an acceptable model fit. The EFA yielded a two-factor solution in both samples, with different items included in each factor for the two samples. Comparison of CFA on the a priori four-factor structure and the new two-factor structure in both samples indicated that both factor structures were of acceptable model fit, with the four-factor model performing slightly better than the two-factor model. CONCLUSION: Factor structure of the MOS-SSS is method-dependent, with CFA supporting a four-factor structure, while EFA yielded a two-factor structure in two separate samples. We need to be careful in selecting the analytic method when applying the MOS-SSS to various samples and choose the factor structure that best fits the theoretical model.

Enabling complex nanoscale pattern customization using directed self-assembly.

Block copolymer directed self-assembly is an attractive method to fabricate highly uniform nanoscale features for various technological applications, but the dense periodicity of block copolymer features limits the complexity of the resulting patterns and their potential utility. Therefore, customizability of nanoscale patterns has been a long-standing goal for using directed self-assembly in device fabrication. Here we show that a hybrid organic/inorganic chemical pattern serves as a guiding pattern for self-assembly as well as a self-aligned mask for pattern customization through cotransfer of aligned block copolymer features and an inorganic prepattern. As informed by a phenomenological model, deliberate process engineering is implemented to maintain global alignment of block copolymer features over arbitrarily shaped, 'masking' features incorporated into the chemical patterns. These hybrid chemical patterns with embedded customization information enable deterministic, complex two-dimensional nanoscale pattern customization through directed self-assembly.

Determination of the internal morphology of nanostructures patterned by directed self assembly.

The directed self-assembly (DSA) of block copolymers (BCP) is an emerging resolution enhancement tool that can multiply or subdivide the pitch of a lithographically defined chemical or topological pattern and is a resolution enhancement candidate to augment conventional lithography for patterning sub-20 nm features. Continuing the development of this technology will require an improved understanding of the polymer physics involved as well as experimental confirmation of the simulations used to guide the design process. Both of these endeavors would be greatly facilitated by a metrology, which is capable of probing the internal morphology of a DSA film. We have developed a new measurement technique, resonant critical-dimension small-angle X-ray scattering (res-CDSAXS), to evaluate the 3D buried features inside the film. This is an X-ray scattering measurement where the sample angle is varied to probe the 3D structure of the film, while resonant soft X-rays are used to enhance the scattering contrast. By measuring the same sample with both res-CDSAXS and traditional CDSAXS (with hard X-rays), we are able to demonstrate the dramatic improvement in scattering obtained through the use of resonant soft X-rays. Analysis of the reciprocal space map constructed from the res-CDSAXS measurements allowed us to reconstruct the complex buried features in DSA BCP films. We studied a series of DSA BCP films with varying template widths, and the internal morphologies for these samples were compared to the results of single chain in mean-field simulations. The measurements revealed a range of morphologies that occur with changing template width, including results that suggest the presence of mixed morphologies composed of both whole and necking lamella. The development of res-CDSAXS will enable a better understanding of the fundamental physics behind the formation of buried features in DSA BCP films.

Three-dimensional nanofabrication by block copolymer self-assembly.

Thin films of block copolymers are widely seen as enablers for nanoscale fabrication of semiconductor devices, membranes, and other structures, taking advantage of microphase separation to produce well-organized nanostructures with periods of a few nm and above. However, the inherently three-dimensional structure of block copolymer microdomains could enable them to make 3D devices and structures directly, which could lead to efficient fabrication of complex heterogeneous structures. This article reviews recent progress in developing 3D nanofabrication processes based on block copolymers.

Two-dimensional pattern formation using graphoepitaxy of PS-b-PMMA block copolymers for advanced FinFET device and circuit fabrication.

Directed self-assembly (DSA) of lamellar phase block-co-polymers (BCPs) can be used to form nanoscale line-space patterns. However, exploiting the potential of this process for circuit relevant patterning continues to be a major challenge. In this work, we propose a way to impart two-dimensional pattern information in graphoepitaxy-based lamellar phase DSA processes by utilizing the interactions of the BCP with the template pattern. The image formation mechanism is explained through the use of Monte Carlo simulations. Circuit patterns consisting of the active region of Si FinFET transistors, referred to as Si "fins", were fabricated to demonstrate the applicability of this technique to the formation of complex patterns. The quality of the Si fin features produced by this process was validated by demonstrating the first functional DSA-patterned FinFET devices with 29 nm-pitch fins.

Programmable nanoparticle ensembles via high-throughput directed self-assembly.

We present a simple and facile strategy for the directed self-assembly of nanoparticles into complex geometries using a minimal set of post guiding features patterned on a substrate. This understanding is based on extensive studies of nanoparticle self-assembly into linear, dense-packed, circular, and star-shaped ensembles when coated onto patterned substrates of predefined post arrays. We determined the conditions under which nanoparticles assemble and "connect" two adjacent post features, thereby forming the desired shapes. We demonstrate that with rational design of the post patterns to enforce the required pairwise interactions with posts, we can create arbitrary arrangements of nanoparticles-for example, to write "IBM" in a deterministic manner. This demonstration of programmable, high-throughput directed self-assembly of nanoparticles shows an alternative route to generate functional nanoparticle assemblies.

High-throughput directed self-assembly of core-shell ferrimagnetic nanoparticle arrays.

Magnetic nanoparticles (MNPs) provide a set of building blocks for constructing stimuli-responsive nanoscale materials with properties that are unique to this scale. The size and the composition of MNPs are tunable to meet the requirements for a range of applications including biosensors and data storage. Although many of these technologies would significantly benefit from the organization of nanoparticles into higher-order architectures, the precise placement and arrangement of nanoparticles over large areas of a surface remain a challenge. Herein, we demonstrate the viability of magnetic nanoparticles for patterned recording media utilizing a template-directed self-assembly process to afford well-defined nanostructures of magnetic nanoparticles and access these assemblies using magnetic force microscopy and a magnetic recording head. Photolithographically defined holes were utilized as templates to form assemblies of ferrimagnetic nanoparticle rings or pillars selectively over a large area (>1 cm(2)) in just 30 s. This approach is applicable to other nanoparticle systems as well and enables their high-throughput self-assembly for future advanced device fabrication.

Pattern placement accuracy in block copolymer directed self-assembly based on chemical epitaxy.

The realization of viable designs for circuit patterns using the dense features formed by block copolymer directed self-assembly (DSA) will require a precise and quantitative understanding of self-assembled feature registration to guiding templates or chemical prepatterns. Here we report measurements of DSA placement error for lamellar block copolymer domains indexed to specific lines in the surface chemical prepattern for spatial frequency tripling and quadrupling. These measurements are made possible by the use of an inorganic domain-selective prepattern material that may be imaged upon polymer removal after DSA and a prepattern design incorporating a single feature serving as an in situ registration mark that is identifiable by pattern symmetry in both the prepattern and resulting self-assembled pattern. The results indicate that DSA placement error is correlated with average prepattern line width as well as prepattern pitch uniformity. Finally, the magnitude of DSA placement error anticipated for a uniform, optimized prepattern is estimated.

Simple and versatile methods to integrate directed self-assembly with optical lithography using a polarity-switched photoresist.

We report novel strategies to integrate block copolymer self-assembly with 193 nm water immersion lithography. These strategies employ commercially available positive tone chemically amplified photoresists to spatially encode directing information into precise topographical or chemical prepatterns for the directed self-assembly of block copolymers. Each of these methods exploits the advantageous solubility and thermal properties of polarity-switched positive tone photoresist materials. Precisely registered, sublithographic self-assembled structures are fabricated using these versatile integration schemes which are fully compatible with current optical lithography patterning materials, processes, and tooling.

Patterning sub-10 nm line patterns from a block copolymer hybrid.

We report the formation and directed self-assembly of sub-10 nm half-pitch line patterns from lamellar microdomains of a block copolymer hybrid. The hybrid, which is a mixture of poly(styrene-b-ethylene oxide) (PS-b-PEO) and a low molecular weight organosilicate (OS), shows strong segregation between two phases (i.e. PS and PEO+OS) and forms lamellar microdomains of down to approximately 7 nm in half-pitch. Patterns applicable to multifinger device layouts are created by self-assembling the hybrid on topographic pre-patterns with a chemically non-selective surface. With careful design of the guiding topographic pattern geometry, well-controlled lateral placement including bent structures of lamellar microdomains can be obtained by this approach.

Three-dimensional self-assembly of spherical block copolymer domains into V-shaped grooves.

The self-assembly of a spherical-morphology block copolymer into V-shaped grooves has been investigated. Although spherical morphology block copolymers typically form a bcc sphere array in bulk, the V groove promotes the formation of a well-ordered fcc close-packed sphere array with the (111) planes of the array parallel to the groove walls. The sphere size in the block copolymer adjusts depending on the commensurability between the periodicity of the block copolymer and the film thickness within the V groove. The top surface of the close-packed array, parallel to the substrate, shows a square symmetry, unlike the hexagonal symmetry seen in monolayers of spherical domains, which may provide a useful geometry for block copolymer lithography.