In many companies and organizations, the quantity of data is growing at a persistent speed creating Big Data.
Big Data involves datasets that grow to such an enormous size that it becomes difficult to work with them by using traditional data management applications.
There is an increasing demand to analyze and an organization’s data and business processes, to recognize competitive market movements or to understand Continue reading “The Visualization of Big Data” »
Bayesian Networks (BNs) represent a probabilistic graphical model of relationships among variables of interest that can be used for classifying data, identifying causal relationships and predicting output/outcome, also known as belief networks or cause-effect relationships.
The Bayesian probability is defined as the degree of belief in a particular event while classical probability evaluates the true or physical probability of an event. Continue reading “Bayesian Networks in Medicine” »
Artificial Neural Networks (ANNs) are one of the “hot” topics in creating innovative medical diagnosis and treatment software for patient-centered medicine.
Neural networks are a class of pattern recognition methods to model the biological neuron to process non-linear or chaotic information where no algorithmic solution is possible or the solution is too complex for traditional techniques.
Recent ANN applications include the modeling of the human body recognizing patterns in scans such as MRI, CAT scans or X-rays but are also used for analyzing brain maturation, ultrasound pictures or cardiograms. They are applied to resolve different diagnostic problems such as detection and classification of cancer, cardiovascular diseases and the processing of EEG signals. Continue reading “Neural Networks IV – Medical Innovation of Tomorrow” »
Privacy is defined as the state in which a person or system is not observed or disturbed by others. A policy is a strategy or path of action of the government, business and other institutions that have the goal to influence decisions and actions of other parties.
Artificial neural networks (ANN) imitate the principles of the biological brain and are progressively more applied across research, medical, engineering, social science and other fields. They also deliver substantial benefits in business applications.
Today’s world is multifaceted and there are countless inter-related variables that make predicting business outcomes very difficult. ANNs are the modern computational tools to study data and develop models to identify patterns and structures in data that offer Continue reading “Neuronal Networks in Business and Marketing” »
Despite the best precautions, it must be accepted and understood that security incidents will happen. It is essential to have the team contact information as well as technologies in place to detect and respond to incidents before any incident happens. It was shown to be valuable to create scenarios and procedures for testing the Incident Response Plan (IRP) and to keep and up-date records that are associated with security incidents and risk measures.
Any IRP should designate a team and define their roles after a security incident, how to document incidents, and how to notify external entities. Continue reading “HIPAA Security V – What is a HIPAA Incident Response Plan?” »
Both, the learning of human neurons and artificial neural networks (ANNs) occur in a training phase and an operation phase. Feed-forward ANNs are very steady and may range over multiple units without having any feedback connections present whereas recurrent ANNs, that do contain feedback connections and provide dynamic network components, that allow developing a dynamic behavior of output patterns of the neural network.
An ANN learns “off-line” if the learning and operation phases are separate and it learns “on-line” if learning and operating are performed at the same time Continue reading “Artificial Neural Networks – Learning Smart” »
The Department of Human Health Services (HHS) requires the mitigation of any risk and vulnerability within an organization that creates, stores and receives electronic Privacy Health Information (ePHI) to reduce harmful effects of security breaches and ePHI violations.
Mitigation procedures may include, but are not limited to, functional and technical corrective measures, employment actions (training procedures, terminations etc.), and inviting business associates into the dialogue to make them aware of a security breach.
Any mitigation should include all characteristics of the HIPAA Security Rule such as administrative policies and procedures, physical workstation security and media control and technical safeguards Continue reading “HIPAA Security IV – What is HIPAA Mitigation?” »
The software development principle of continuous delivery is a team effort to create and maintain an automated building, testing and deployment of code and software.
Using continuous delivery guarantees that software is released long before users are given access to it and that additional releases occur very frequently – not less than once per iteration but normally as often as several times a day. Software is continuously tested for functionality Continue reading “The Continuous Delivery Pipeline” »
Cloud computing is for sure the next generation of delivering IT services. Many companies already started to outsource data and software hoping for a better data management and cost reduction. However, many questions arise around cloud security and it seems to be inevitable that Security as a Service becomes important for both data and infrastructure security and compliance for cloud providers and users.
There are three general concern areas of cloud security: “Security and Privacy” Continue reading “Security as a Service – How secure is the cloud?” »