El Gusanillo Lector

Up to the present, SCD cannot be cured completely, but with a proper management regimen, enhanced by advanced analytical techniques such as artificial intelligence, the severity of the condition can be mitigated, leading to improvements in the quality of care. The vast majority of patients with more severe SCD symptoms benefit from taking a medicine called hydroxyurea [39]. This method of pharmacotherapy has been shown to be effective at reducing the number of painful crises and raising the number of haemoglobin and Fetal haemoglobin (HB F) within patient’s blood[40]. According to the medical community, Hydroxyurea is mainly prescribed to prevent painful crises [36]. Interventions in the last two decades have gradually reduced

15 | P a g e mortality, particularly in children, and the recommendations remain in progress [41]. Early identification is clearly required and can provide a good opportunity for clinicians to mitigate the disease. In this respect, parents are required to observer their children carefully at home and seek advice if they observe respiratory symptoms or fever, in addition to ensuring effective hydration.

Early diagnosis can prevent a number of complications that sickle cell patients could face in the future. The best way to diagnose sickle cell traits or sickle cell disease is through a simple blood test. In order to diagnose all mothers in the first few weeks of pregnancy, doctors and nurses use a tissue taken from the placenta or sample of amniotic fluid. The placenta is a temporary organ that is located in the mother's womb. Internationally and across the UK indeed, most of the Women’s hospitals and clinical sectors use advanced screening programs to check new-born babies against SCD. In this context, if the blood test sample shows that an infant carries sickle haemoglobin (Hb S), or sickle haemoglobin traits (HbAS), a second blood test required in order to confirm the diagnosis.

One of the most significant solutions to achieve this challenge is to develop web-based applications to allow healthcare professionals to monitor the vast majority of patients instead of using old-fashioned paper-based methods. This modern technology provides a proper treatment, preventing test duplication and communicating with patients during critical conditions. Technological solutions should be designed based on the local realities in order to achieve the main aims of healthcare development. The web-based system consists of different kind of support interface for patients and physicians. A graph representation is integrated within the web system to provide patients with a view of the overall activities. On the other hand, all patients’ data transfer to the web-based network interface used by medical experts, which can deal with patients’ responses through a user-friendly layout. Such applications could enhance healthcare services, have the potential impact on reducing professional isolation particularly in remote locations, and offer ongoing support for the clinicians as well as the community.

2.5.1 Limitations and Challenges in Medical Sector

Communication plays an important and major role in healthcare organisations. One of the most significant challenges facing healthcare sectors is that there is still insufficient communication between the patients and medical doctors [42]. Furthermore, there are still a number of barriers to obtaining excellent communication and relationships between patients and medical experts [43]. Miscommunication has potential implications, as it can set false expectations of treatment,

16 | P a g e and hinder patients' understanding and involvement in treatment planning [44]. In addition, these situations may lead to a decreased level of confidence and reduce patient satisfaction with health care. The current situation in healthcare environment is divided into 4 steps:

• Up to this date, there is no intelligent system that has been used yet in terms of managing SCD. However, this research provides a system that facilitates a shift from manual input methods to an expert approach that can analyse patient’s blood sample with a reduced error rate

• The most challenging aspect that is facing healthcare these days is that, there is still insufficient communication between the SCD patients and associated healthcare providers.

• Currently there is no standardisation of disease modifying therapy management.

• There is still a need for developing an intelligent SCD diagnosis system that is eligible to provide a specific treatment plan inspired by an expert system.

The specific purpose of communication between SCD patients and doctors can be identified in association with exchanging vital information and providing related treatment. Healthcare professionals tend to communicate with their patients in order to offer optimal therapy and provide accurate decisions based on quick assessment [45]. Improved patient-doctor communications approaches intend to raise adherence and involvement in recommended treatment, build trust, and enhance health outcomes and the quality of health.

2.5.2 Challenges of Datasets in the Clinical Domain

Information technology and clinical datasets offer good services and assistance for the medical domain in many applications. However, there are some limitations for using healthcare datasets. Firstly, the medical datasets are not filtered and not ready to be analysed using machine learning algorithms. The main reason behind that is because the vast majority of medical data are heterogeneous. A number of SCD patients’ blood test results are in numeric form, images and text form. The processing of such datasets is a challenge to developers. To solve this problem, some studies suggested that a data warehouse needed to be built before the dataset procedure. therefore, this issue may not reliable and can be time consuming for previous data [46]. Secondly, the nature of data is not processed (unrecognized data), comprises corrupted files, missing features values, and inconsistent with family history or patient history [24]. Thirdly, medical data needs expert people that can integrate knowledge in the medical

17 | P a g e science domain to understand the structure of datasets along with features and class labels and need knowledge in the computer science field to be able to use different types of techniques to analyse the SCD dataset.

Typically, this field is computation techniques utilising experience to enhance performance, for instance to make correct predictions and classification. The motivation for using machine- learning techniques is to handle a potentially unbounded amount of data and process them to achieve the same accuracy and performance. Machine learning consists of utilising classification techniques (classifier) to group a set of symbols into a number of classes depending on their attributes (features). A feature is considered one aspect of a symbol that can help in aggregating it according to each class. One of the significant factors that has a strong influence on the success of a learning method is the type of data that is used to represent the task to be learned.

2.5.3 Motivation

The motivation for building a system for patients and clinicians came after meeting with a number of clinicians and specialist nurses across NHS domain to understand the level of support available to patients with SCD; and the resources existing to medical doctors. Currently, all hospitals and healthcare sectors are using manual approaches that depend completely on medical consultant’s experience, which can be slow to analyse, time consuming and stressful. This project has been proposed to the Alder Hey Children’s Hospital and the Royal Liverpool Hospital. It soon emerged that some aspects of the current schemes needed improvement but could increase cost.

Moreover, this multifaceted research study is intended to improve our experiences and knowledge. Although the proposed system employed in solving the issues in medical domain, it is believed that this study could pose some important challenges for those who are suffering from sickle cell disease. There are many way to classifying SCD datasets such as machine learning models and statistical metechinques. However, the main reason of slection machine learning in the proposed study due to producing better accuracy and performance.