Medicaid

Multitask Artificial Intelligence–Based Electrocardiogram Tool for Preoperative Cardiac Testing in Noncardiac Surgery: Retrospective Cohort Study of Health Care Utilization and Costs

Preoperative cardiovascular (CV) risk stratification is essential in non-cardiac surgery, but conventional testing is frequently overused, increasing costs without improving outcomes. Artificial intelligence (AI)-enabled electrocardiography (ECG) may enhance perioperative risk assessment by identifying patients at very low risk for adverse events. This study aimed to evaluate whether AI-ECG-based ...

Improving Quantization-aware Training of Low-Precision Network via Block Replacement on Full-Precision Counterpart

Quantization-aware training (QAT) is a common paradigm for network quantization, in which the training phase incorporates the simulation of the low-precision computation to optimize the quantization parameters in alignment with the task goals. However, direct training of low-precision networks generally faces two obstacles: 1. The low-precision model exhibits limited representation capabilities ...

PETALface: Parameter Efficient Transfer Learning for Low-resolution Face Recognition

Pre-training on large-scale datasets and utilizing margin-based loss functions have been highly successful in training models for high-resolution fa...

Leveraging Content and Context Cues for Low-Light Image Enhancement

Low-light conditions have an adverse impact on machine cognition, limiting the performance of computer vision systems in real life. Since low-light ...

Frequency-Adaptive Low-Latency Object Detection Using Events and Frames

Fusing Events and RGB images for object detection leverages the robustness of Event cameras in adverse environments and the rich semantic informatio...

Low-Resolution Object Recognition with Cross-Resolution Relational Contrastive Distillation

Recognizing objects in low-resolution images is a challenging task due to the lack of informative details. Recent studies have shown that knowledge ...

What Makes a Face Look like a Hat: Decoupling Low-level and High-level Visual Properties with Image Triplets

In visual decision making, high-level features, such as object categories, have a strong influence on choice. However, the impact of low-level featu...

Machine learning models for differential diagnosing HER2-low breast cancer: A radiomics approach.

To develop machine learning models based on preoperative dynamic enhanced magnetic resonance imaging (DCE-MRI) radiomics and to explore their potentia...

Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.

There is no study that comprehensively evaluates data on the readability and quality of "palliative care" information provided by artificial intellige...

[Intelligent intensive care unit makes medicine more accessible].

In the past half century, critical care medicine has made rapid development, and the survival rate of critically ill patients has significantly improv...

Probing the Relationship Between Latent Linear Dynamical Systems and Low-Rank Recurrent Neural Network Models.

A large body of work has suggested that neural populations exhibit low-dimensional dynamics during behavior. However, there are a variety of different...

Prior knowledge facilitates low homologous protein secondary structure prediction with DSM distillation.

MOTIVATION: Protein secondary structure prediction (PSSP) is one of the fundamental and challenging problems in the field of computational biology. Ac...

Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review.

Skin cancers occur commonly worldwide. The prognosis and disease burden are highly dependent on the cancer type and disease stage at diagnosis. We sys...

Advancing care for acute gastrointestinal bleeding using artificial intelligence.

The future of gastrointestinal bleeding will include the integration of machine learning algorithms to enhance clinician risk assessment and decision ...

The Potential of AI in Care Optimization: Insights from the User-Driven Co-Development of a Care Integration System.

Transitions from one level of care to another are complex processes that pose medical and organizational risks and depend on care integration between ...

Characterizing Subgroups of High-Need, High-Cost Patients Based on Their Clinical Conditions: a Machine Learning-Based Analysis of Medicaid Claims Data.

Comparison of Machine Learning Algorithms for the Prediction of Preventable Hospital Readmissions.

A diverse universe of statistical models in the literature aim to help hospitals understand the risk factors of their preventable readmissions. Howeve...

[Recognition of Low Arousal Level Electroencephalogram in the Vigilance Based on Wavelet Packet Rhythm and Support Vector Machine].

Poor and monotonous work could easily lead to a decrease of arousal level of the monitoring work personnel. In order to improve the performance of mon...

Understanding Emergency Department 72-Hour Revisits Among Medicaid Patients Using Electronic Healthcare Records.

Electronic Healthcare Records (EHRs) have the potential to improve healthcare quality and to decrease costs by providing quality metrics, discovering ...