Precision medicine is a process that involves the derivation of novel taxonomies based on deep phenotyping. It aims to improve healthcare by using large-scale data, including clinical, lifestyle, genetic, and biomarker information, to stratify patients into subgroups that may respond differently to treatments. This approach goes beyond the traditional "signs-and-symptoms" method and incorporates a wide array of individual data to enable more precise therapeutic strategies. The term "precision medicine" is often confused with related concepts such as "stratified medicine," "targeted therapy," and "deep phenotyping." However, precision medicine is defined as a process that includes the derivation of novel taxonomies and their role in healthcare as part of a cycle, along with related terms. The process of precision medicine involves three tracks: preprocessing and data mining, diagnostic and prognostic models, and predicting treatment response. In the first track, data are processed and mined to identify patterns and structures. In the second track, models are developed to predict disease outcomes or treatment responses. In the third track, models are used to predict how well specific patients will respond to treatment. These models are validated in independent samples to ensure their reliability and effectiveness. Deep phenotyping is a key component of precision medicine, involving the comprehensive and fine-grained description of individuals. This includes data from various sources such as genetic, clinical, and environmental factors. The integration of these data allows for the identification of disease subgroups that can be treated more effectively. Examples from asthma and chronic obstructive pulmonary disease (COPD) illustrate how precision medicine can improve patient care by tailoring treatments to individual needs. The development and validation of diagnostic and prognostic models require transparent reporting and clinical utility. These models should be tested in independent samples to ensure their effectiveness and should be disseminated to be used in clinical practice. Precision medicine is not a static endpoint but a continuous process that involves feedback loops and ongoing efforts to improve precision and individualization of care. The ultimate goal is to provide more effective and personalized treatment strategies for patients.Precision medicine is a process that involves the derivation of novel taxonomies based on deep phenotyping. It aims to improve healthcare by using large-scale data, including clinical, lifestyle, genetic, and biomarker information, to stratify patients into subgroups that may respond differently to treatments. This approach goes beyond the traditional "signs-and-symptoms" method and incorporates a wide array of individual data to enable more precise therapeutic strategies. The term "precision medicine" is often confused with related concepts such as "stratified medicine," "targeted therapy," and "deep phenotyping." However, precision medicine is defined as a process that includes the derivation of novel taxonomies and their role in healthcare as part of a cycle, along with related terms. The process of precision medicine involves three tracks: preprocessing and data mining, diagnostic and prognostic models, and predicting treatment response. In the first track, data are processed and mined to identify patterns and structures. In the second track, models are developed to predict disease outcomes or treatment responses. In the third track, models are used to predict how well specific patients will respond to treatment. These models are validated in independent samples to ensure their reliability and effectiveness. Deep phenotyping is a key component of precision medicine, involving the comprehensive and fine-grained description of individuals. This includes data from various sources such as genetic, clinical, and environmental factors. The integration of these data allows for the identification of disease subgroups that can be treated more effectively. Examples from asthma and chronic obstructive pulmonary disease (COPD) illustrate how precision medicine can improve patient care by tailoring treatments to individual needs. The development and validation of diagnostic and prognostic models require transparent reporting and clinical utility. These models should be tested in independent samples to ensure their effectiveness and should be disseminated to be used in clinical practice. Precision medicine is not a static endpoint but a continuous process that involves feedback loops and ongoing efforts to improve precision and individualization of care. The ultimate goal is to provide more effective and personalized treatment strategies for patients.