AIMC Topic: Machine Learning

Clear Filters Showing 33331 to 33340 of 34417 articles

Towards rapid prediction of drug-resistant cancer cell phenotypes: single cell mass spectrometry combined with machine learning.

Chemical communications (Cambridge, England)
Combined single cell mass spectrometry and machine learning methods is demonstrated for the first time to achieve rapid and reliable prediction of the phenotype of unknown single cells based on their metabolomic profiles, with experimental validation...

A Machine Learning Recommender System to Tailor Preference Assessments to Enhance Person-Centered Care Among Nursing Home Residents.

The Gerontologist
BACKGROUND AND OBJECTIVES: Nursing homes (NHs) using the Preferences for Everyday Living Inventory (PELI-NH) to assess important preferences and provide person-centered care find the number of items (72) to be a barrier to using the assessment.

Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse.

Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco
INTRODUCTION: Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological moment...

Detecting Brain Tumor using Machines Learning Techniques Based on Different Features Extracting Strategies.

Current medical imaging reviews
BACKGROUND: Brain tumor is the leading cause of death worldwide. It is obvious that the chances of survival can be increased if the tumor is identified and properly classified at an initial stage. MRI (Magnetic Resonance Imaging) is one source of bra...

An Intensity Variation Pattern Analysis Based Machine Learning Classifier for MRI Brain Tumor Detection.

Current medical imaging reviews
BACKGROUND: An accurate detection of tumor from the Magnetic Resonance Images (MRIs) is a critical and demanding task in medical image processing, due to the varying shape and structure of brain. So, different segmentation approaches such as manual, ...

Three Dimensional Analysis of SPECT Images for Diagnosing Early Parkinson's Disease using Radial Basis Function Kernel - Extreme Learning Machine.

Current medical imaging reviews
BACKGROUND: Parkinson's Disease (PD) is caused by the deficiency of dopamine, the neurotransmitter that has an effect on specific uptake region of the substantia nigra. Identification of PD is quite tough at an early stage.

Categorization & Recognition of Lung Tumor Using Machine Learning Representations.

Current medical imaging reviews
BACKGROUND: Lung Cancer is the disease spreading around the world nowadays. Early recognition of lung disease is a difficult task as the cells which cause tumor will grow quickly and the majority of these cells are enclosed with each other. From the ...

A Hybrid Approach for Sub-Acute Ischemic Stroke Lesion Segmentation Using Random Decision Forest and Gravitational Search Algorithm.

Current medical imaging reviews
BACKGROUND: The sub-acute ischemic stroke is the most basic illnesses reason for death on the planet. We evaluate the impact of segmentation technique during the time of breaking down the capacities of the cerebrum.