Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid disease predictions. A systematic literature review (SLR) strategy is used in this study to give a comprehensive overview of the existing literature on forecasting data on thyroid disease diagnosed using ML. This study includes 168 articles published between 2013 and 2022, gathered from high-quality journals and applied meta-analysis. The thyroid disease diagnoses (TDD) category, techniques, applications, and solutions were among the many elements considered and researched when reviewing the 41 articles of cited literature used in this research. According to our SLR, the current technique's actual application and efficacy are constrained by several outstanding issues associated with imbalance. In TDD, the technique of ML increases data-driven decision-making. In the Meta-analysis, 168 documents have been processed, and 41 documents on TDD are included for observation analysis. The limits of ML that are discussed in the discussion sections may guide the direction of future research. Regardless, this study predicts that ML-based thyroid disease detection with imbalanced data and other novel approaches may reveal numerous unrealised possibilities in the future
Background: Changes in the indication for splenectomy in hematology, especially in hematological malignancies, has been observed in the last 10 – 15 years. Yet splenectomy, as a diagnostic tool, is still an option in the management of isolated splenomegaly.
Objectives: to describe the outcome of diagnostic splenectomy in the management of 12 patients presenting with isolated splenomegaly.
Patients and methods: Between August 2005 and July2012, Twelve patients underwent splenectomy for diagnostic purposes in the hematology unit / Baghdad Teaching Hospital. Analysis of these patients was done with a median follow up of 16 months (6 months -4 years).
Results: The median age was 46 years (range 25-68). The median duration of sympt
In this paper , certain subclass of harmonic multivalent function defined in the exterior of the unit disk by used generalize hypergeometric functions is introduced . In This study an attempting have been made to investigate several geometric properties such as coefficient property , growth bounds , extreme points , convolution property , and convex linear combination .
Due to the vast using of digital images and the fast evolution in computer science and especially the using of images in the social network.This lead to focus on securing these images and protect it against attackers, many techniques are proposed to achieve this goal. In this paper we proposed a new chaotic method to enhance AES (Advanced Encryption Standards) by eliminating Mix-Columns transformation to reduce time consuming and using palmprint biometric and Lorenz chaotic system to enhance authentication and security of the image, by using chaotic system that adds more sensitivity to the encryption system and authentication for the system.
In this work, we consider a modification of the Lotka-Volterra food chain model of three species, each of them is growing logistically. We found that the model has eight equilibrium points, four of them always exist, while the rest exist under certain conditions. In terms of stability, we found that the system has five unstable equilibrium points, while the rest points are locally asymptotically stable under certain satisfying conditions. Finally, we provide an example to support the theoretical results.
Background: Zinc is involved in a variety of
metabolic processes and it has a well known
antioxidant activity, so the measurement of its serum
level can have a special value in several diseases.
Objectives: The study is designed to determine the
serum zinc level in heart failure patients and to
compare it with that of healthy individuals and to
study the significance of the results obtained.
Methods: Atomic absorption spectrometer
technique was used to determine serum zinc level in
fifty heart failure patients and fifty healthy individuals
who were age and sex matched.
Results: The mean serum zinc level in healthy
individuals was about 45.5% greater than that of heart
failure patients. This diffe
Background: Infectious mononucleosis (IM) is a lymphoproliferative disease caused primarily by the Epstein-Barr virus (EBV) infection. The initial viral infection by EBV occurs in B lymphocytes and is followed by an extensive proliferation of T lymphocytes. Previous studies on immunity to EBV (including IM) have mainly focused on activation of peripheral blood T cells, which are responsible for the lymphocytosis in blood during acute IM.
Patients and Methods: Indirect immunofluorescence technique analysis was performed to detect the percentage of CD3, CD4, CD8, CD19, and CD56 positive lymphocytes.
Results: Our results on the phenotype of T cells in samples from patients with infectious mononucleosis sh
Many fuzzy clustering are based on within-cluster scatter with a compactness measure , but in this paper explaining new fuzzy clustering method which depend on within-cluster scatter with a compactness measure and between-cluster scatter with a separation measure called the fuzzy compactness and separation (FCS). The fuzzy linear discriminant analysis (FLDA) based on within-cluster scatter matrix and between-cluster scatter matrix . Then two fuzzy scattering matrices in the objective function assure the compactness between data elements and cluster centers .To test the optimal number of clusters using validation clustering method is discuss .After that an illustrate example are applied.
Background: Cerebral ischemia associated with Antiphospholipid Syndrome(APS) is a common arterial manifestation in adults.
Objectives: To look for the frequency of Antiphospholipid Antibodies (aPL), and their relation with other risk factors in young patients with cerebral ischemia.
Patients and methods: A retrospective study of 40 young patient’s ≤ 50 years with stroke collected from medical and neurological wards of Baghdad Teaching Hospital (BTH) from January - December 2009. All were inquired about the presence of risk factors of stroke, and sent for aPL including Anticardiolipin (ACL) and Lupus Anticoagulant (LA).
Results: Eight (20%) had ACL. Nine (22.5%) had LA. Both were present in 6(15%). ACL and/or LA were present
Making the data secure is more and more concerned in the communication era. This research is an attempt to make a more secured information message by using both encryption and steganography. The encryption phase is done with dynamic DNA complementary rules while DNA addition rules are done with secret key where both are based on the canny edge detection point of the cover image. The hiding phase is done after dividing the cover image into 8 blocks, the blocks that are used for hiding selected in reverse order exception the edge points. The experiments result shows that the method is reliable with high value in PSNR