Geriatrics

Medicare

Latest AI and machine learning research in medicare for healthcare professionals.

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Geriatrics Subcategories: Alzheimer's Disease Medicare
Showing 85-105 of 3,442 articles
SH: Long-tailed classification via spatial constraint sampling, scalable network, and hybrid task.

Long-tailed classification is a significant yet challenging vision task that aims to making the clea...

ResGloTBNet: An interpretable deep residual network with global long-range dependency for tuberculosis screening of sputum smear microscopy images.

Tuberculosis is a high-mortality infectious disease. Manual sputum smear microscopy is a common and ...

Evaluation of deep learning-based scatter correction on a long-axial field-of-view PET scanner.

OBJECTIVE: Long-axial field-of-view (LAFOV) positron emission tomography (PET) systems allow higher ...

Toward Machine Learning Electrospray Ionization Sensitivity Prediction for Semiquantitative Lipidomics in Stem Cells.

Specificity, sensitivity, and high metabolite coverage make mass spectrometry (MS) one of the most v...

Deep reinforcement learning for time-critical wilderness search and rescue using drones.

Traditional search and rescue methods in wilderness areas can be time-consuming and have limited cov...

Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach.

Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke...

MDWConv:CNN based on multi-scale atrous pyramid and depthwise separable convolution for long time series forecasting.

Long time series forecasting has extensive applications in various fields such as power dispatching,...

Ecological risks of PFAS in China's surface water: A machine learning approach.

The persistence of per- and polyfluoroalkyl substances (PFAS) in surface water can pose risks to eco...

The advantages of lexicon-based sentiment analysis in an age of machine learning.

Assessing whether texts are positive or negative-sentiment analysis-has wide-ranging applications ac...

Coverage bias in small molecule machine learning.

Small molecule machine learning aims to predict chemical, biochemical, or biological properties from...

ImpACT Project: Improving Access to Clinical Trials in Victoria, an Artificial Intelligence-Based Approach.

PURPOSE: Enhancing the speed and efficiency of clinical trial recruitment is a key objective across ...

Forecasting O and NO concentrations with spatiotemporally continuous coverage in southeastern China using a Machine learning approach.

Ozone (O) is a significant contributor to air pollution and the main constituent ofphotochemical smo...

BiGM-lncLoc: Bi-level Multi-Graph Meta-Learning for Predicting Cell-Specific Long Noncoding RNAs Subcellular Localization.

The precise spatiotemporal expression of long noncoding RNAs (lncRNAs) plays a pivotal role in biolo...

Optimizing sequence data analysis using convolution neural network for the prediction of CNV bait positions.

BACKGROUND: Accurate prediction of copy number variations (CNVs) from targeted capture next-generati...

Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).

To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning sy...

Cooperative control of self-learning traffic signal and connected automated vehicles for safety and efficiency optimization at intersections.

Cooperative control of intersection signals and connected automated vehicles (CAVs) possess the pote...

Robust long-tailed recognition with distribution-aware adversarial example generation.

Confronting adversarial attacks and data imbalances, attaining adversarial robustness under long-tai...

Predicting Early Hospital Discharge Following Revision Total Hip Arthroplasty: An Analysis of a Large National Database Using Machine Learning.

BACKGROUND: Revision total hip arthroplasty (rTHA) was recently removed from the Medicare inpatient-...

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