Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Tumour heterogeneityTumour heterogeneity describes the observation that different tumour cells can show distinct morphological and phenotypic profiles, including cellular morphology, gene expression, metabolism, motility, proliferation, and metastatic potential. This phenomenon occurs both between tumours (inter-tumour heterogeneity) and within tumours (intra-tumour heterogeneity). A minimal level of intra-tumour heterogeneity is a simple consequence of the imperfection of DNA replication: whenever a cell (normal or cancerous) divides, a few mutations are acquired—leading to a diverse population of cancer cells.
Somatic evolution in cancerSomatic evolution is the accumulation of mutations and epimutations in somatic cells (the cells of a body, as opposed to germ plasm and stem cells) during a lifetime, and the effects of those mutations and epimutations on the fitness of those cells. This evolutionary process has first been shown by the studies of Bert Vogelstein in colon cancer. Somatic evolution is important in the process of aging as well as the development of some diseases, including cancer. Cells in pre-malignant and malignant neoplasms (tumors) evolve by natural selection.
Germline mutationA germline mutation, or germinal mutation, is any detectable variation within germ cells (cells that, when fully developed, become sperm and ova). Mutations in these cells are the only mutations that can be passed on to offspring, when either a mutated sperm or oocyte come together to form a zygote. After this fertilization event occurs, germ cells divide rapidly to produce all of the cells in the body, causing this mutation to be present in every somatic and germline cell in the offspring; this is also known as a constitutional mutation.
Hereditary nonpolyposis colorectal cancerHereditary nonpolyposis colorectal cancer (HNPCC) or Lynch syndrome is an autosomal dominant genetic condition that is associated with a high risk of colon cancer as well as other cancers including endometrial cancer (second most common), ovary, stomach, small intestine, hepatobiliary tract, upper urinary tract, brain, and skin. The increased risk for these cancers is due to inherited genetic mutations that impair DNA mismatch repair. It is a type of cancer syndrome.
Feature learningIn machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process.
Pancreatic neuroendocrine tumorPancreatic neuroendocrine tumours (PanNETs, PETs, or PNETs), often referred to as "islet cell tumours", or "pancreatic endocrine tumours" are neuroendocrine neoplasms that arise from cells of the endocrine (hormonal) and nervous system within the pancreas. PanNETs are a type of neuroendocrine tumor, representing about one-third of gastroenteropancreatic neuroendocrine tumors (GEP-NETs). Many PanNETs are benign, while some are malignant. Aggressive PanNET tumors have traditionally been termed "islet cell carcinoma".
Renal cell carcinomaRenal cell carcinoma (RCC) is a kidney cancer that originates in the lining of the proximal convoluted tubule, a part of the very small tubes in the kidney that transport primary urine. RCC is the most common type of kidney cancer in adults, responsible for approximately 90–95% of cases. RCC occurrence shows a male predominance over women with a ratio of 1.5:1. RCC most commonly occurs between 6th and 7th decade of life. Initial treatment is most commonly either partial or complete removal of the affected kidney(s).
Feedforward neural networkA feedforward neural network (FNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. Its flow is uni-directional, meaning that the information in the model flows in only one direction—forward—from the input nodes, through the hidden nodes (if any) and to the output nodes, without any cycles or loops, in contrast to recurrent neural networks, which have a bi-directional flow.
MutationIn biology, a mutation is an alteration in the nucleic acid sequence of the genome of an organism, virus, or extrachromosomal DNA. Viral genomes contain either DNA or RNA. Mutations result from errors during DNA or viral replication, mitosis, or meiosis or other types of damage to DNA (such as pyrimidine dimers caused by exposure to ultraviolet radiation), which then may undergo error-prone repair (especially microhomology-mediated end joining), cause an error during other forms of repair, or cause an error during replication (translesion synthesis).
