AIMC Topic: Algorithms

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Spectral-Spatial Features Integrated Convolution Neural Network for Breast Cancer Classification.

Sensors (Basel, Switzerland)
Cancer identification and classification from histopathological images of the breast depends greatly on experts, and computer-aided diagnosis can play an important role in disagreement of experts. This automatic process has increased the accuracy of ...

Clinical and Research Medical Applications of Artificial Intelligence.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Artificial intelligence (AI), including machine learning (ML), has transformed numerous industries through newfound efficiencies and supportive decision-making. With the exponential growth of computing power and large datasets, AI has transitioned fr...

Calculation of immune cell proportion from batch tumor gene expression profile based on support vector regression.

Journal of bioinformatics and computational biology
In addition to tumor cells, a large number of immune cells are found in the tumor microenvironment (TME) of cancer patients. Tumor-infiltrating immune cells play an important role in tumor progression and patient outcome. We improved the relative pro...

Machine learning models predicting multidrug resistant urinary tract infections using "DsaaS".

BMC bioinformatics
BACKGROUND: The scope of this work is to build a Machine Learning model able to predict patients risk to contract a multidrug resistant urinary tract infection (MDR UTI) after hospitalization. To achieve this goal, we used different popular Machine L...

Data integration by fuzzy similarity-based hierarchical clustering.

BMC bioinformatics
BACKGROUND: High throughput methods, in biological and biomedical fields, acquire a large number of molecular parameters or omics data by a single experiment. Combining these omics data can significantly increase the capability for recovering fine-tu...

Exploiting bi-directional global transition patterns and personal preferences for missing POI category identification.

Neural networks : the official journal of the International Neural Network Society
Recent years have witnessed the increasing popularity of Location-based Social Network (LBSN) services, which provides unparalleled opportunities to build personalized Point-of-Interest (POI) recommender systems. Existing POI recommendation and locat...

Event-driven H control with critic learning for nonlinear systems.

Neural networks : the official journal of the International Neural Network Society
In this paper, we study an event-driven H control problem of continuous-time nonlinear systems. Initially, with the introduction of a discounted cost function, we convert the nonlinear H control problem into an event-driven nonlinear two-player zero-...

GeFeS: A generalized wrapper feature selection approach for optimizing classification performance.

Computers in biology and medicine
In this paper, we propose a generalized wrapper-based feature selection, called GeFeS, which is based on a parallel new intelligent genetic algorithm (GA). The proposed GeFeS works properly under different numerical dataset dimensions and sizes, care...

Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank.

IEEE journal of biomedical and health informatics
Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide since first reported. Timely diagnosis of COVID-19 is crucial both for disease control and patient care. Non-contrast thoracic computed tomography (CT) has been identified as an effecti...

A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis.

Artificial intelligence in medicine
Deregulated splicing machinery components have shown to be associated with the development of several types of cancer and, therefore, the determination of such alterations can help the development of tumor-specific molecular targets for early prognos...