China 
Africa 
Explore chapters and articles related to this topic
Smart Functionalised-Dendrimeric Medicine in Cancer Therapy
Published in Neelesh Kumar Mehra, Keerti Jain, Dendrimers in Nanomedicine, 2021
Vijay Mishra, Manvendra Singh, Pallavi Nayak
Cancer is the uncontrolled development of abnormal cells with a faster rate as compared to normal cells. Such abnormal cells damage the healthy tissues of the body and promote the expansion of cancer (Figure 13.2). According to the prevalent cancer hypothesis, normal cells transform to cancerous cells via irregular structural, molecular and biochemical networking (Rajani et al. 2020). The group of cancerous cells forming an abnormal mass of tissues is considered as ‘solid tumour’, while the abnormal cells that do not form any mass of tissue are ‘leukaemia’ or blood cancer. Depending on their cell type, tumours are classified as malignant and benign tumours. A malignant tumour is a cancerous tumour, which can invade its surrounding tissues and spread all over the body. A new tumour forms, when a malignant tumour separated out from the parent tumour and passes through the lymphatic system (or blood) from their main site to another site. The benign tumour is a non-cancerous tumour, which does not grow and spread like malignant tumours. If the infected cells exert pressure on the vital organs, the benign tumour can become more harmful. Gene mutation caused by heritage or non-heritage factors is responsible for the growth and proliferation of anomalous cells (Rajani et al. 2020).
An Automated Hybrid Methodology Using Firefly Based Fuzzy Clustering for Demarcation of Tissue and Tumor Region in Magnetic Resonance Brain Images
Published in J. Dinesh Peter, Steven Lawrence Fernandes, Carlos Eduardo Thomaz, Advances in Computerized Analysis in Clinical and Medical Imaging, 2019
Saravanan Alagarsamy, Kartheeban Kamatchi, Vishnuvarthanan Govindaraj
The malignant tumors are diagnosed by computerized tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI). Different types of image sequence can be done for patients to obtain the required information for decision making. MRI tends to be a more effective technique for early diagnosis of tumor [2]. But brain tumor with different grades and volume remain a challenge for MRI diagnosis. For particular cases, MRI technique is not sufficient for decision making and some manual assistance is required for accurate brain tumor segmentation. Demarcation of brain tumor is a very difficult task for analyzing the medical images. There is a need of an automated segmentation technique for identifying the tumor and tissue regions present in MR brain image. Such problem can be effectively handled with the help of recommended Firefly based IT2FCM [3].
Health Risk Assessment
Published in Theodore Louis, Behan Kelly, Introduction to Optimization for Environmental and Chemical Engineers, 2018
Cancer is a disease of individual cells, and even one cell can grow and divide many times to produce a new cancer mass. Thus, the cure can be accomplished only by removing or killing every single malignant cell. The three accepted ways of doing this are surgery, radiation, and drugs, which are often used in combination. Several dozen drugs are used at present to treat cancer, and research has shown just how the drugs should be used for best effect. The size and timing of each dose may have profound effects on drug action, as may the drug’s integration with surgical or radiation treatment. Moreover, because some of the drugs attack cancer cells in different ways, the use of as many as four or five such drugs in a precisely determined combination or sequence is commonly more effective than the use of just one.
Novel computer aided diagnostic system using hybrid neural network for early detection of pancreatic cancer
Published in Automatika, 2023
To monitor, forecast, and categorize the presence of pancreatic tumours, automated classification of pancreatic tumours using computer-aided diagnostic models (CAD) is necessary [4–8]. One of the worst diseases with one of the lowest survival rates at the moment is pancreatic cancer, which is now incurable. The type of treatment needed will depend on the tumour's size, location, and whether it has spread to other parts of the body. In the case of pancreatic cancer, healthy cells in the organ begin to malfunction and proliferate uncontrollably. These malignant cells can accumulate and develop into a mass known as a tumour. Malignant refers to the ability of a cancerous tumour to develop and metastasize to other areas of the body. A pancreatic tumour can eventually migrate to other areas of the body through a process known as metastasis, which can also cause it to damage the pancreas’ ability to function [9–12].
EWPCO-enabled Shepard convolutional neural network for classification of brain tumour using MRI image
Published in The Imaging Science Journal, 2023
K. Mohana Sundaram, R. Sasikumar
The traditional and the latest MRI scans are used to determine the dimension, type, malignancy grade, and location of the tumour. Moreover, MRI scans are frequently utilized to differentiate Low-Grade Gliomas(LGGs) from High-Grade Gliomas (HGGs) [7]. MRI scans also called MRI sequences, capture different positions of cancers depending on various time, and intensity framework in which every sequence is considered crucial in the prediction of various cancer sub-areas [8, 9]. The scan offers hundreds of two-dimensional (2D) image slices with high soft tissue difference utilizing no ionizing radiation in MRI acquisition [10, 11]. MRI scanning is helpful for disease diagnosis and categorization because of its high resolution when compared to other technologies. MRI scans employ non-ionizing radiations and magnetic fields to obtain the sight of different tissues and organs. The outcomes of MRI scanning are soft tissues of the body in the form of 3D images. Soft tissues are absolutely muscles and organs, which cannot be anticipated in the images acquired by X-rays. For this reason, MRI images are commonly utilized for classifying brain tumours in medical applications. Brain is one of the most significant organs in the human body that control numerous complicated tasks. MRI method has been effectively used to recognize numerous diseases in the brain, especially tumours. Identifying brain tumours in earlier from MRI images has newly obtained important significance and is considered a lifesaver for brain cancer patients. However, the classification of brain tumours is important; it is similarly essential to find the tumours type to enhance the survival rate of patients and suggest regular therapy [1, 12, 13].
Synthesis of N-doped carbon dots for highly selective and sensitive detection of metronidazole in real samples and its cytotoxicity studies
Published in Environmental Technology, 2022
Xiaoxiang Wang, Tao Lin, Wei Wu, Haisuo Wu, Dongdong Yan
Moreover, the current society is facing difficulties in getting rid-off another health problem is cancer. Every year, 38 million people died of non-pandemic diseases. Major cases are related to the cancer [3]. The recorded death rate due to the cancer was 8.2 million, and there is a maximum probability for a further rise in case number because approximately 14 million cases are recorded all-over the world currently [4]. A huge number of cancerous cases are detected in cervical, breast, lung, stomach, and cervix. The conventional treatment for these types is radiation therapy, surgical operation, and chemotherapeutic drugs, which may influence the benign and malignant cells. Besides, treatment via these methods face serious limitations on the bioavailability of the drug at the targeted site due to its lower soluble nature, and it further led to the non-addressed activity of drugs [5], which could influence the daily activities of body organs. In general, nanomaterials usually stay farther in cancer cells than normal cells due to their Enhanced Permeability and Retention effect [6]. The common facility with nanomaterials is that the tiny size and large surface area may permit facile manipulation for positive and determined purposes without or with minimal unwanted issues [7,8]. Thus, among various types of nanomaterials, carbon dots (CDs) have been attracting great attention due to their good photostability, promising fluorescence nature, biocompatibility, high water solubility when compared to conventional organic dyes and metal-based quantum dots [9–15]. Also, CDs have good application potentials in different areas such as sensing, nanocarriers, biomedical, and photo-electronic devices [16–19]. Also, the surface passivation with functional groups drives them to serve as a specific molecule recogniser for sensing applications.