Medicaid

Building Prediction Models for 30-Day Readmissions Among ICU Patients Using Both Structured and Unstructured Data in Electronic Health Records.

ICU readmissions are associated with poor outcomes for patients and poor performance of hospitals. Patients who are readmitted have an increased risk of in-hospital deaths; hospitals with a higher read-mission rate have a reduced profitability, due to an increase in cost and reduced payments from Medicare and Medicaid programs. Predicting a patient's likelihood of being readmitted to the ICU can h...

Impact of low pneumoperitoneum on renal function and acute kidney injury biomarkers during robot-assisted radical prostatectomy (RARP): a randomised clinical trial.

The objective of this study was to evaluate the effect of low pneumoperitoneum pressure (Pnp) on renal function and renal injury biomarkers during robot-assisted radical prostatectomy (RARP). A single-centre, triple-blinded, randomised clinical trial was conducted with 98 patients undergoing RARP, who were assigned to either standard Pnp of 12 mmHg or low Pnp of 7 mmHg. The primary outcome was uri...

Machine Learning-Based Predictive Models for 90-Day Readmission of Total Joint Arthroplasty Using Comprehensive Electronic Health Records and Patient-Reported Outcome Measures.

BACKGROUND: The Centers for Medicare & Medicaid Services currently incentivizes hospitals to reduce postdischarge adverse events such as unplanned hos...

Rapid analysis of hydrogen cyanide in fresh cassava roots using NIRSand machine learning algorithms: Meeting end user demand for low cyanogenic cassava.

This study focuses on meeting end-users' demand for cassava (Manihot esculenta Crantz) varieties with low cyanogenic potential (hydrogen cyanide poten...

Application of statistical machine learning in biomarker selection.

In the recent JAVELIN Bladder 100 phase 3 trial, avelumab plus best supportive care significantly prolonged overall survival relative to best supporti...

Beyond SEP-1 Compliance: Assessing the Impact of Antibiotic Overtreatment and Fluid Overload in Suspected Septic Patients.

BACKGROUND: The Centers for Medicare and Medicaid Services (CMS) developed the Severe Sepsis and Septic Shock Performance Measure bundle (SEP-1) metri...

Optical imaging technologies for cancer detection in low-resource settings.

Cancer continues to affect underserved populations disproportionately. Novel optical imaging technologies, which can provide rapid, non-invasive, and ...

Fast and Calibrationless Low-Rank Parallel Imaging Reconstruction Through Unrolled Deep Learning Estimation of Multi-Channel Spatial Support Maps.

Low-rank technique has emerged as a powerful calibrationless alternative for parallel magnetic resonance (MR) imaging. Calibrationless low-rank recons...

Actionable artificial intelligence: Overcoming barriers to adoption of prediction tools.

Clinical prediction models based on artificial intelligence algorithms can potentially improve patient care, reduce errors, and add value to the healt...

HER2-low breast cancer: insights on pathological testing.

Human epidermal growth factor receptor 2 (HER2) is an important biomarker for predicting prognosis and effectiveness of HER2-targeted therapy in breas...

Deep Learning-Enabled Multiplexed Point-of-Care Sensor using a Paper-Based Fluorescence Vertical Flow Assay.

Multiplexed computational sensing with a point-of-care serodiagnosis assay to simultaneously quantify three biomarkers of acute cardiac injury is demo...

Low temperature decreased insecticidal protein contents of cotton and its physiological mechanism.

Low temperature delayed cotton growth, increased abscission of reproductive organs, and seriously reduced quality and yield. Moreover, failed or unsta...

Relating local connectivity and global dynamics in recurrent excitatory-inhibitory networks.

How the connectivity of cortical networks determines the neural dynamics and the resulting computations is one of the key questions in neuroscience. P...

Low SNR Multi-Emitter Signal Sorting and Recognition Method Based on Low-Order Cyclic Statistics CWD Time-Frequency Images and the YOLOv5 Deep Learning Model.

It is difficult for traditional signal-recognition methods to effectively classify and identify multiple emitter signals in a low SNR environment. Thi...

Effective Training of Convolutional Neural Networks With Low-Bitwidth Weights and Activations.

This paper tackles the problem of training a deep convolutional neural network of both low-bitwidth weights and activations. Optimizing a low-precisio...

Low precision decentralized distributed training over IID and non-IID data.

Decentralized distributed learning is the key to enabling large-scale machine learning (training) on the edge devices utilizing private user-generated...

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool that empowers Frontline-Health-Workers (FHW). This...

The impact of sparsity in low-rank recurrent neural networks.

Neural population dynamics are often highly coordinated, allowing task-related computations to be understood as neural trajectories through low-dimens...

Emphysema Quantification Using Ultra-Low-Dose Chest CT: Efficacy of Deep Learning-Based Image Reconstruction.

Background and Objectives: Although reducing the radiation dose level is important during diagnostic computed tomography (CT) applications, effective ...

Using natural language processing to identify acute care patients who lack advance directives, decisional capacity, and surrogate decision makers.

The prevalence of patients who are Incapacitated with No Evident Advance Directives or Surrogates (INEADS) remains unknown because such data are not r...