Artificial Intelligence Algorithms and the Biomedical World
Introduction
The classic magic trick of putting in life into an inanimate object has fascinated the world for ages but what seemed like magic just a few years ago is the new reality. The advancement in the recent technologies harness the potential to add life to the metallic bodies namely machines giving the ability to not only function but alluringly, think independently and even take decisions with their rationality through a set of predefined instructions called Algorithms. The rules are the Skeletor foundation which governs the brain of the system called the Artificial Neural Network thus, acting like the soul of the machine body.
Artificial Neural Network: The brain of the future
A neural network is composed of multiple processing units called nodes which are present within the combination of several layers that processes the input provided by the user on the basis of the value assigned to the variable according to the mathematical formula for the weight of the node. If the calculated value exceeds the threshold formula, the input gets passed on to the next node which marks a cycle of the transfer of data until an appropriate value (the desired output) is reached. Thus, transfer of signal from input to output is achieved through transmission of values within different nodes.
The functioning of artificial neural network finds inspirations from the functioning of the brain. The nodes of the ANN are like neurons of the brain which are connected through the synapses that transmit signals. While the brain is highly structured, a simple neutral network consists of an input layer, output layer and a hidden layer that learns through training using algorithms that adjust weights of the nodes to give the required outputs.
ChatGPT: A Case Study
ChatGPT is a remarkable AI model that engages algorithms like self-attention mechanisms and transformer architectures which gives it the ability to relate distant elements in sequences and form relationships thus, providing an understanding of complex patterns and assigning appropriate weights to each element based on the relevancy which helps the system to cope with the long-term memory loss as a result of vanishing gradient problem as the recurrent neural network is unable to process the intact sentence as a whole.
ChatGPT: A biomedical tool with endless possibilities
ChatGPT has immense potential as a biomedical and bioinformatics research tool in the domain of biomedical and bioinformatics. Different sectors like Drug discovery, Genetics and Omics (analysis of living organisms) can be hugely benefitted through artificial algorithms through the enormous collection of data libraries stored in the memory that enables finding correlations and patterns that otherwise difficult to find through traditional techniques. It not only reduces the tedious tasks of manually assessing and diagnosing but also decreases the room of error and mistakes thus, making the system more efficient and increasing the capacity for diagnosing complex diseases faster than the traditional methods and also developing targeted therapies based on the range of accurate symptoms obtained from the database.
ANN: Close but not close enough
The artificial intelligence models have undetermined potential to revolutionize the healthcare industries, yet they lack empathy and human intuition and instincts, which makes unable to take critical decisions that requires complex understanding and analyzing of the situations. Accessing the present technologies, the ANN can be a reputed asset for the medical professionals.
Conclusion
Artificial intelligence algorithm model is a virtual artificial brain which is an asset to biomed and healthcare industries. it not only shows immense potential as a research tool and ease the tedious process like diagnosing that requires utmost precision, but also provide assistance like symptom tracking, providing with appropriate coping strategies and assist in complex procedures requiring precisions.
References:
https://www.cloudflare.com/en-gb/learning/ai/what-is-neural-network/
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