An international team of researchers led by Dr. Nischalan Pillay (UCL Cancer Institute) and Dr. Ludmil Alexandrov (University of California, San Diego) used AI to identify 21 frequent faults in the structure, order, and quantity of copies of DNA present when cancer begins and progresses. These widespread errors, known as copy number signatures, could help doctors find medicines that match the tumor's characteristics. As the Netflix algorithm suggests new videos on the basis of a person's like and dislikes, the researchers developed a similar algorithm that can filter through thousands of lines of genomic data to find common patterns in the way chromosomes organize and arrange themselves. The system may then classify the patterns that develop, assisting scientists in determining the types of cancer faults that can form. DNA alterations, such as gains and losses, frequently occur in cancer and result from a variety of interconnected events, including replication stress, mitotic mistakes, spindle multipolarity, and breakage–fusion–bridge cycles, which can cause chromosomal instability and aneuploidy.