Researchers have proposed a diagnostic tool that can produce diagnostic results within just two minutes. This is according to the research paper published in a journal named Analytical Chemistry by researchers at Swansea University. These researchers are developing a tool that uses artificial intelligence can detect various biomarkers that are present in different biofluids. The diagnostic tool will be using the analytical and decision-making abilities of AI and machine learning to rapidly analyze the biofluid samples within just a couple of minutes. AI or artificial intelligence has many advantages in performing repetitive tasks. It can maintain the accuracy of a particular task even after performing it hundreds of times. Along with this, AI can also improve itself every time by using machine learning abilities to get more accurate over time. Because of this, AI is a perfect tool for performing healthcare testing procedures that are repetitive and require precision. For its use in healthcare, AI can be trained using large sets of data and operating guidelines. Hence the researchers at Swansea University have decided to use the capabilities of AI to perform diagnostic procedures. As proposed in the published research paper, biofluids such as synovial fluid, blood plasma, and saliva contain proteins, which contain various biomarkers such as various proteins and DNA. This diagnostic tool uses AI to detect and analyze the concentration of various biomarkers in a biofluid sample. Based on this, the diagnostic results of respective patients are produced. As this procedure involves an AI instead of an actual human, the whole procedure can be completed within a few minutes. Dr. Francesco Del Giudice, who is the head of this project, stated that the existing method of detecting macromolecules such as proteins from biofluids takes a lot of time and requires specific complex formations for detection, thus increasing the tediousness of the procedure. Further continuing, Francesco said that the method they have developed uses only around 100 mL of the sample which is equivalent to just two drops of biofluids and provides results in just 2 minutes instead of the hours required using conventional methods. The implications of such technology are in clinical trials, where tremendously large sets of data are analyzed daily. Using AI will help clinicians in decision-making based on the rapidly generated clinical data. Dr. Claire Barnes, the co-author of this paper stated that AI has shown that it can be used to dial down the time required for completing any tedious procedures in several disciplines. Using machine learning along with artificial intelligence allows researchers to implement real-time testing parameters with AI procedures to generate more accurate results, fulfilling the requirements of the theoretical structure. She further continued that for now, the AI with machine learning used in this diagnostic tool is only limited to the automation of processes. But in the future, this AI can use its machine learning capabilities to learn from large sets of data and mimic human intelligence and assist in decision-making based on the results. The implementation of AI into the system has opened several possibilities for a diagnostic tool. It will be interesting to see how these researchers develop their tools in the future to assist healthcare in day-to-day life.