Machine learning (ML) is a branch of artificial intelligence that uses an algorithm to process the data, retrieve valuable information, learn from it, find a pattern, and make predictions. Manual data analyses suffer from several disadvantages including it is time-consuming and subject to error.

Lung cancer is the leading cause of cancer death among both men and women in the United States. Because lung cancer is genetically heterogeneous, tailored therapy alone or in combination with chemotherapy would increase patient overall survival as compared with the one-size-fits-all chemotherapy. TP53-mutant lung cancer accounts for more than half of all lung cancer cases and is oftentimes more aggressive and resistant to chemotherapy. Directly targeting mutant p53 has not yet been successful, so identification of novel therapy targets and biomarkers in the TP53-mutant lung cancer is urgently needed to increase the overall survival in this subgroup.

Arthritis remains a common and debilitating disease affecting millions of people worldwide. Osteoarthritis (OA) and rheumatoid arthritis (RA) are among the most common forms of this chronic, degenerative disease, which is moving toward precision medicine.

New stool DNA panels and blood-based assays offer non-invasive options for early CRC detection, though require further validation. Immuno- and targeted therapies matched to tumor molecular profiles have transformed metastatic CRC treatment. Pembrolizumab elicits durable responses in mismatch repair-deficient tumors, and anti-EGFR antibodies cetuximab/panitumumab improve outcomes for left-sided RAS/RAF wild-type CRC. Larotrectinib and entrectinib are highly active in NTRK fusion-positive CRC. Research focusing on new immunotherapies, leveraging the microbiome, and combining multi-omics data to enable precision medicine holds promise. Disparities across groups remain a challenge.