CIC 2023: Enhancing Referrals to the Supplemental Nutrition Assistance Program (SNAP) through Clinical Integration of a Standards-Based Decision Support System.

Background: The Supplemental Nutrition Assistance Program (SNAP) is one of the most successful national programs to reduce poverty and improve health outcomes, but millions of Americans who qualify still do not have access to SNAP, and limited data is available to determine how referrals to the program can be completed successfully.

Objectives: We aimed to design and develop a standards-based digital care coordination platform to support closed-loop social services referrals between patients and social and health care providers; and demonstrate the feasibility to screen, diagnose, plan, and complete interventions with selected patients in real-settings.

Methods: We partnered with community members to design the platform through Community Engagement Studios and with a Federally Qualified Health Center, Local Mental Health Authority, and Food Bank to determine the features and workflow requirements of the platform design.

Taste Masking Study of Orally Disintegrating Film (ODF) Formulations Containing Memantine Hydrochloride.

Geriatric patients have difficulty to comply to their medication regimen due to complicated medication administration schedule, dysphagia, reduced ability to swallow tablets and dementia. This is particularly more challenging among the Alzheimer Disease's patients. Therefore, a model drug, memantine hydrochloride has been formulated into an orally disintegrating film (ODF) for easier consumption.

A Comprehensive Review of Challenges in Oral Drug Delivery Systems and Recent Advancements in Innovative Design Strategies.

The oral route of drug administration is often preferred by patients and healthcare providers due to its convenience, ease of use, non-invasiveness, and patient acceptance. However, traditional oral dosage forms have several limitations, including low bioavailability, limited drug loading capacity, and stability and storage issues, particularly with solutions and suspensions. Over the years, researchers have dedicated considerable effort to developing novel oral drug delivery systems to overcome these limitations.

Leading edge of the a-wave of the electroretinogram and sodium iodate-induced age-related macular degeneration: A model.

Background: Iron-induced oxidative stress was thought to be the reason why the a-wave amplitude of the electroretinogram (ERG) dropped when iron ions were present. It is assumed that reactive oxygen species (ROS) are generated in the presence of iron ions, and this leads to a decrease in hyperpolarization of the photoreceptor. It is known that in age-related macular degeneration (AMD), sodium iodate can induce oxidative stress, apoptosis, and retinal damage, which mimic the effects of clinical AMD.

BraNet: a mobil application for breast image classification based on deep learning algorithms.

Mobile health apps are widely used for breast cancer detection using artificial intelligence algorithms, providing radiologists with second opinions and reducing false diagnoses. This study aims to develop an open-source mobile app named "BraNet" for 2D breast imaging segmentation and classification using deep learning algorithms. During the phase off-line, an SNGAN model was previously trained for synthetic image generation, and subsequently, these images were used to pre-trained SAM and ResNet18 segmentation and classification models.

Economic Burden of Mosquito-Borne Diseases in Low- and Middle-Income Countries: Protocol for a Systematic Review.

Background: Globally, among all the vector-borne diseases, mosquito-borne diseases are responsible for a substantial number of cases and deaths and amount to an economic cost of US $12 billion per year. However, there is a dearth of systematic research conducted on the economic burden of mosquito-borne diseases. To address the lack of comprehensive information on this topic, a systematic review will be conducted to synthesize evidence for informing targeted policies and strategies addressing this growing burden and for better financial protection of households.

OW-SLR: Overlapping Windows on Semi-Local Region for Image Super-Resolution.

There has been considerable progress in implicit neural representation to upscale an image to any arbitrary resolution. However, existing methods are based on defining a function to predict the Red, Green and Blue (RGB) value from just four specific loci. Relying on just four loci is insufficient as it leads to losing fine details from the neighboring region(s).

Social and Health Information Platform: Piloting a Standards-Based, Digital Platform Linking Social Determinants of Health Data into Clinical Workflows for Community-Wide Use.

Background: Social determinants of health (SDoH)a are increasingly recognized as a main contributor to clinical health outcomes, but the technologies and workflows within clinics make it difficult for health care providers to address SDoH needs during routine clinical visits.

Objectives: Our objectives were to pilot a digital platform that matches, links, and visualizes patient-level information and community-level deidentified data from across sectors; establish a technical infrastructure that is scalable, generalizable, and interoperable with new datasets or technologies; employ user-centered codesign principles to refine the platform's visualizations, dashboards, and alerts with community health workers, clinicians, and clinic administrators.

Methods: We used privacy-preserving record linkage (PPRL) tools to ensure that all identifiable patient data were encrypted, only matched and displayed with consent, and never accessed or stored by the data intermediary.

Health Care Equity Through Intelligent Edge Computing and Augmented Reality/Virtual Reality: A Systematic Review.

Intellectual capital is a scarce resource in the healthcare industry. Making the most of this resource is the first step toward achieving a completely intelligent healthcare system. However, most existing centralized and deep learning-based systems are unable to adapt to the growing volume of global health records and face application issues.

Preliminary Report on Optical Coherence Tomography Angiography Biomarkers in Non-Responders and Responders to Intravitreal Anti-VEGF Injection for Diabetic Macular Oedema.

Purpose: To identify optical coherence tomography angiography (OCTA) biomarkers in patients who were treated for diabetic macular oedema (DME) with intravitreal anti-vascular endothelial growth factor (VEGF) injections and compare the OCTA parameters between responders and non-responders.

Methods: A retrospective cohort study of 61 eyes with DME who received at least one intravitreal anti-VEGF injection was included between July 2017 and October 2020. The subjects underwent a comprehensive eye examination followed by an OCTA examination before and after intravitreal anti-VEGF injection.

Outcome of Ivermectin in Cancer Treatment: An Experience in Loja-Ecuador.

(1) Background: Cancer is one of the leading causes of death worldwide, and trends in cancer incidence and mortality are increasing over last years in Loja-Ecuador. Cancer treatment is expensive because of social and economic issues which force the patients to look for other alternatives. One such alternative treatment is ivermectin-based antiparasitic, which is commonly used in treating cattle.

Detection and Classification of Knee Osteoarthritis.

Osteoarthritis (OA) affects nearly 240 million people worldwide. Knee OA is the most common type of arthritis, especially in older adults. Physicians measure the severity of knee OA according to the Kellgren and Lawrence (KL) scale through visual inspection of X-ray or MR images.

Frontiers in Retinal Image Processing.

Visual impairment is considered as a primary global challenge in the present era [...

Relationship Between Posterior Vitreous Detachment and Macular Dimensions in Myopic Eyes.

Background: Posterior vitreous detachment (PVD) can result in serious pathologic events at the vitreoretinal interface. This study aims to assess the relationship between PVD, macular thickness (MT), and the foveal avascular zone (FAZ) in myopic eyes.

Methods: This retrospective study evaluated 63 myopic subjects' data who were examined between January 1 and June 30, 2019.

FHIRedApp: a LEAP in health information technology for promoting patient access to their medical information.

Objective: Our aim is to develop a patient engagement technology that makes it easy for patients to access their own medical information and share it with others.

Materials And Methods: This paper describes our design through an adapted Community Engagement Studio methodology to identify the needs and preferences of a diverse group of Latinx, African-American, and Asian-American individuals in the community. We use Human-Centered Design to interpret these needs and preferences to build a digital app platform, using national data standards, clinical data aggregators, and privacy-preserving solutions while maintaining the security and confidentiality of patients.

FAZSeg: A New Software for Quantification of the Foveal Avascular Zone.

Introduction: Various ocular diseases and high myopia influence the anatomical reference point Foveal Avascular Zone (FAZ) dimensions. Therefore, it is important to segment and quantify the FAZs dimensions accurately. To the best of our knowledge, there is no automated tool or algorithms available to segment the FAZ's deep retinal layer.

The [Formula: see text]-Wave of the Electroretinogram and Iron-Induced Oxidative Stress: A Model.

In photoreceptors of a dark adapted eye, the inward flux of sodium and calcium ions in the outer segment is balanced by the outward flux of potassium ions. But in the presence of light the creation of cyclic guanosine monophosphate in the outer segment decreases. Due to low concentration of cG (cyclic GMP) the channels in the outer segment open relatively less and thus the influx of calcium ion decreases, leading finally to hyperpolarization of the photoreceptors.

ODTiD: Optic Nerve Head SD-OCT Image Dataset.

Introduction: Optic disc tilt (ODT) or tilted optic disc is a common finding in the general population. It is due to anomalous development caused by the malclosure of the embryonic optic fissure. ODT is commonly associated with high myopia as well as other conditions.

Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey.

Diabetic Retinopathy (DR) is a leading cause of vision loss in the world. In the past few years, artificial intelligence (AI) based approaches have been used to detect and grade DR. Early detection enables appropriate treatment and thus prevents vision loss.

Gelation Kinetics-Structure Analysis of pH-triggered Low Molecular Weight Hydrogelators.

Properties such as shear modulus, gelation time, structure of supramolecular hydrogels are strongly dependent on self-assembly, gelation triggering mechanism and processes used to form the gel. In our work we extend reported rheology analysis methodologies to pH-triggered supramolecular gels to understand structural insight using a model system based on N-N' Dibenzoyl-L-Cystine pH-triggered hydrogelator and Glucono-δ-Lactone as the trigger. We observed that Avrami growth model when applied to time-sweep rheological data of gels formed at lower trigger concentrations provide estimates of fractal dimension which agree well compared with visualization of the microstructure as seen via Confocal Laser Scanning Microscopy, for a range of gelator concentrations.

Evaluation of Explainable Deep Learning Methods for Ophthalmic Diagnosis.

Background: The lack of explanations for the decisions made by deep learning algorithms has hampered their acceptance by the clinical community despite highly accurate results on multiple problems. Attribution methods explaining deep learning models have been tested on medical imaging problems. The performance of various attribution methods has been compared for models trained on standard machine learning datasets but not on medical images.

Rapid classification of glaucomatous fundus images.

We propose a new method for training convolutional neural networks (CNNs) and use it to classify glaucoma from fundus images. This method integrates reinforcement learning along with supervised learning and uses it for transfer learning. The training method uses hill climbing techniques via two different climber types, namely, "random movement" and "random detection," integrated with a supervised learning model through a stochastic gradient descent with momentum model.