AIMC Topic: Support Vector Machine

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A Spacecraft Electrical Characteristics Multi-Label Classification Method Based on Off-Line FCM Clustering and On-Line WPSVM.

PloS one
This paper proposes a novel multi-label classification method for resolving the spacecraft electrical characteristics problems which involve many unlabeled test data processing, high-dimensional features, long computing time and identification of slo...

Close Human Interaction Recognition Using Patch-Aware Models.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This paper addresses the problem of recognizing human interactions with close physical contact from videos. Due to ambiguities in feature-to-person assignments and frequent occlusions in close interactions, it is difficult to accurately extract the i...

Mortality Prediction in ICUs Using A Novel Time-Slicing Cox Regression Method.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Over the last few decades, machine learning and data mining have been increasingly used for clinical prediction in ICUs. However, there is still a huge gap in making full use of the time-series data generated from ICUs. Aiming at filling this gap, we...

Data-driven Temporal Prediction of Surgical Site Infection.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Analysis of data from Electronic Health Records (EHR) presents unique challenges, in particular regarding nonuniform temporal resolution of longitudinal variables. A considerable amount of patient information is available in the EHR - including blood...

Interpretable Probabilistic Latent Variable Models for Automatic Annotation of Clinical Text.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We propose Latent Class Allocation (LCA) and Discriminative Labeled Latent Dirichlet Allocation (DL-LDA), two novel interpretable probabilistic latent variable models for automatic annotation of clinical text. Both models separate the terms that are ...

Automated Reconciliation of Radiology Reports and Discharge Summaries.

AMIA ... Annual Symposium proceedings. AMIA Symposium
We study machine learning techniques to automatically identify limb abnormalities (including fractures, dislocations and foreign bodies) from radiology reports. For patients presenting to the Emergency Room (ER) with suspected limb abnormalities (e.g...

A hybrid manifold learning algorithm for the diagnosis and prognostication of Alzheimer's disease.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The diagnosis of Alzheimer's disease (AD) requires a variety of medical tests, which leads to huge amounts of multivariate heterogeneous data. Such data are difficult to compare, visualize, and analyze due to the heterogeneous nature of medical tests...

TWSVR: Regression via Twin Support Vector Machine.

Neural networks : the official journal of the International Neural Network Society
Taking motivation from Twin Support Vector Machine (TWSVM) formulation, Peng (2010) attempted to propose Twin Support Vector Regression (TSVR) where the regressor is obtained via solving a pair of quadratic programming problems (QPPs). In this paper ...

A Novel Characteristic Frequency Bands Extraction Method for Automatic Bearing Fault Diagnosis Based on Hilbert Huang Transform.

Sensors (Basel, Switzerland)
Because roller element bearings (REBs) failures cause unexpected machinery breakdowns, their fault diagnosis has attracted considerable research attention. Established fault feature extraction methods focus on statistical characteristics of the vibra...

Color Correction Parameter Estimation on the Smartphone and Its Application to Automatic Tongue Diagnosis.

Journal of medical systems
BACKGROUND: An automatic tongue diagnosis framework is proposed to analyze tongue images taken by smartphones. Different from conventional tongue diagnosis systems, our input tongue images are usually in low resolution and taken under unknown lightin...