Neural Networks and Immunotherapy
Okay, that just sounds like two completely unrelated disciplines being thrown together or maybe you have absolutely no idea what it is at all. Well, in that case, let’s review what we mean by both neural networks and immunotherapy before we move on to how they correlate.
Neural Networks are computing systems built to imitate the functioning of an animal brain by simulating a circuit of neurons or artificial neural networks as weights between nodes.
Neural Networks can recognize and establish relationships and correlations between large subsets of data and then classify, cluster, or interpret them. Furthermore, they learn with time and hence constantly improve their functioning. As it is easier to regulate the numerous parameters while still maintaining functionality, it’s widely used to synthesize solutions where traditional computer methods cost more time and are less efficient.
A neural network is made up of three main layers — an input layer, a processing layer, and an output layer. The input layer works by weighing within the available inputs based on what is supported by the varied criteria and the processing layer (hidden from view) has nodes and the connections between these nodes are used to exchange information. The nodal collections and information exchanges are meant to be analogous to the neurons and synapses in an animal brain. The output layer works by displaying or utilizing the analyzed, processed data.
Now, neural networks have a wide range of applications starting at finance industries to automotive ones; image recognition to stock market predictors. A relatively recent addition to the list is Immunotherapy. Before we talk about any further developments, let’s take a look at what Immunotherapy is.
Immunotherapy is the manipulation (suppression or activation) of certain parts of the body’s immune system to fight the disease. It is a widely used treatment for cancer.
Now that we have a rough idea of what immunotherapy and neural networks are, let’s talk about how neural networks and machine learning overall have been helpful for immunotherapy. Neural networks have long been helpful in recent advancements in medicine. With the advancements of artificial intelligence and deep learning because of neural networks, assessments can be standardized across different institutions. Although we still have a long way to go in integrating the diverse biomarkers into one system, machine learning still makes imaging and treatment significantly easier by identifying the immune cell types in different parts of the body and how involved they are in different diseases. The algorithms can then also proceed to predict the different immune trajectories which helps in administering the appropriate treatments. Scientists reckon that this might be key in understanding the molecular pathways as the building blocks of disease.
That’s it for today, but there is a lot more ground to cover when it comes to advancements in medicine and the integration of artificial intelligence in the same. Perhaps some other day at LetsUpgrade.
- Vinita Rajan