AIMC Topic: Neural Networks, Computer

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Use of an Artificial Neural Network to Construct a Model of Predicting Deep Fungal Infection in Lung Cancer Patients.

Asian Pacific journal of cancer prevention : APJCP
BACKGROUND: The statistical methods to analyze and predict the related dangerous factors of deep fungal infection in lung cancer patients were several, such as logic regression analysis, meta-analysis, multivariate Cox proportional hazards model anal...

Multiprocessor Neural Network in Healthcare.

Studies in health technology and informatics
A possible way of creating a multiprocessor artificial neural network is by the use of microcontrollers. The RISC processors' high performance and the large number of I/O ports mean they are greatly suitable for creating such a system. During our res...

Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

Combinatorial chemistry & high throughput screening
The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this ...

Personalized decision support system based on clinical practice guidelines.

Studies in health technology and informatics
Personalized medicine is a broad and rapidly advancing field of health care that is informed by each person's unique clinical, genetic, genomic, and environmental information. Health care that embraces personalized medicine is an integrated, coordina...

Supervised machine learning algorithms to diagnose stress for vehicle drivers based on physiological sensor signals.

Studies in health technology and informatics
Machine learning algorithms play an important role in computer science research. Recent advancement in sensor data collection in clinical sciences lead to a complex, heterogeneous data processing, and analysis for patient diagnosis and prognosis. Dia...

Optimizing artificial neural network models for metabolomics and systems biology: an example using HPLC retention index data.

Bioanalysis
BACKGROUND: Artificial Neural Networks (ANN) are extensively used to model 'omics' data. Different modeling methodologies and combinations of adjustable parameters influence model performance and complicate model optimization.

Application of artificial neural networks to link genetic and environmental factors to DNA methylation in colorectal cancer.

Epigenomics
AIMS: We applied artificial neural networks (ANNs) to understand the connections among polymorphisms of genes involved in folate metabolism, clinico-pathological features and promoter methylation levels of MLH1, APC, CDKN2A(INK4A), MGMT and RASSF1A i...

Post-operative bleeding risk stratification in cardiac pulmonary bypass patients using artificial neural network.

Annals of clinical and laboratory science
The prediction of bleeding risk in cardiopulmonary bypass (CPB) patients plays a vital role in their postoperative management. Therefore, an artificial neural network (ANN) to analyze intra-operative laboratory data to predict postoperative bleeding ...

Artificial neural network approach to modelling of metal contents in different types of chocolates.

Acta chimica Slovenica
The relationships between the contents of various metals in different types of chocolates were studied using chemometric approach. Chemometric analysis was based on the application of artificial neural networks (ANN). ANN was performed in order to se...

Assessment of an expert system for the automated validation of electrophoretic profiles.

Clinical laboratory
BACKGROUND: The Core-lab of the Greater Romagna Area Hub Laboratory carries out about 250,000 capillary electrophoresis assays/year. The huge workload demands the assessing of an Experimental Expert System (EES) capable to sort out the negative sampl...