Statistics reveal that every minute a human is losing his/her life across the globe. More close in India, everyday many lives are affected by heart attacks and more importantly because the patients did not get timely and proper help . So a reliable, energy efficient patient monitoring system is designed and developed. It is able to send parameters of patient in real time. It enables the doctors to monitor patient’s health parameters (temp, heartbeat, ECG, position) in real time.
The various applications of ANN in medical diagnosis are: colorectal cancer , multiple sclerosis lesions , colon cancer ,pancreatic disease, gynaecological diseases and early diabetes and many more. GENERAL STRUCTURE: ANN is formed by a series of nodes or neurons made of silicon and wires that are organised in the form of layers one below the other, with the neurons connected to each other through weighted connections . These weight values indicate the strength of connection between the neurons in ith and jth layer ,i.e., next layer . Any neural network basically consists of three main layers that
For patients with chronic diseases, which account for the biggest part of readmissions to the hospital, the monitoring of simple values can heavily support the pre-emptive detection of patient deterioration. Most prominently, renal failure, Septicemia, diabetes, psychotic disorders, airway disease and cardiac disease often result in readmissions to the hospital . The collection of data to support monitoring these diseases at home can range from simple devices, such as digital scales (e.g. to track fluid fluctuations
They can update their knowledge by reading journals for evidence based practice, and participate and conduct research. In my opinion give more awareness to the public that, how an APN will manage patient’s care, diagnosis, treatment to a patient through special workshop, group discussions and media publicity. Make special arrangements in clinic setting through that APNs can promote health awareness, treat and diagnosis for simple cases. All these make patient to increase their confidence and trust on APNs. Moreover, all these helps patient to shortening the waiting time in clinic to consult doctors during their routine visit especially in polyclinic.
1. HEALTHCARE INFORMATICS Healthcare informatics in nursing improves decision making, it helps in detecting changes in patient’s condition which could be for the nurse to call rapid response team or to intervene through modified early warning system (MEWS) which assigns numerical value to the vital signs reading and calculates a score that indicates the severity of the sickness and tendency of escalating to critical condition. Nurse is able to locate essential equipment such as IV pumps, infusion pumps, EKG machines, portable computers with the click of a button when wireless technology and radio frequency identification (RFID) thereby improving patient care at the nursing level. The nurse could equally use RFID technology to track surgical
The CDSS inference engine will accept the patient history, signs, symptoms, and test results from the EMR in real-time, and present the closest case and solution to the physician. The CDSS will match up current symptoms and signs and will place proper alerts and suggestions from within the current EMR. The alerts, informational messages, and diagnosis are based on a sophisticated knowledge base database loaded with evidence-based medical cases designed to work within a wide range of EMR domains. The case-based method allows the addition of revised problem-solution cases, and conversely allows for the soft removal of obsolete problem-solution cases by flagging them as inactive or “forgotten”. Conclusion A system developed using case-based reasoning would be able to provide more comprehensive solutions for users because it has access to knowledge acquired from a vast number of past cases.
It should occur throughout the nursing process as well as at the end. It allows the nurse to evaluate the patient’s response to the nursing interventions that were provided and the progress the patient is making with their treatment. The nurse can then plan further care based on what worked well and what didn’t work for this patient (Ackley and Ladwig, 2014). The nurse evaluated the care that was provided to John. The goal was not met entirely and as a result the care plan was revised by the nurse.
This framework is designed to help the nurse with gathering information and identifying potential challenges of the community. After collecting the data, the nurse will be able to examine the information to create a plan based on the identified issue. Once the plan is implemented, the nurse will have an opportunity to evaluate the effectiveness of the plan by verifying if the desired health outcomes are attained (Yui, 2016). When assessing a community, the nurse can use various methods on how to collect data such as environmental scan, needs assessment, problem investigation, and resource evaluation (Yui, 2016). These four methods are used in combination to assess the Sunset community such as collecting information from various government websites, and articles which contain statistics that has quantitative and qualitative data (Yui, 2016).
Formal assessment tools will help professionals evaluate their patients’ reading and skills abilities, along with their capacity to complete healthcare tasks. Informal strategies will allow specialists identify the red flags that may indicate health literacy challenges, for example when patients recognize medications by looking at them, rather than reading labels (Osborne, 2013). In addition, it is important to involve members of the target audience on the design of health materials, so they can feedback on health communication products and health professionals know what areas they should improve in. Likewise, health providers may invite patients to improve their own health literacy skills, by educating them on how to keep note of their symptoms. Nurses can also help patients create their medical
The acquired spectrum will be used to train the supervised learning Neural Network Toolbox in Simulink and construct an experiment to verify the ANN trained model can classify the oil palm maturity. 3.4. 3 Data processing Artificial Neural Network (ANN) model will be used to manage acquired data. It will process the selection of the input and the output. Besides, the system will trained with this model.