2023, 09 September
Machine learned decision tree for diagnosis of ASM...
Machine learning on electronic health records (EHR) was used to produce a data-driven decision tree (algorithm) to flag high-risk patients for ASMD...
2023, 17 May
Machine Learning (ML) applied to real-world data t...
Newly diagnosed metastatic melanoma patients are often treated with molecular targeted therapy (TT) or with immunotherapy (IO).
2023, 09 May
AI-Powered Pre-Competitive Disease and Care Modeli...
Drugs evaluation has been undergoing a transformational shift from the classical sequence of randomized control trials (RCT) and Real-World (RW) st...
2023, 09 May
Cluster Algorithm for Credible Subgroup Identifica...
This non-comparative, retrospective study aimed to characterize the profiles of erectile disfunction (ED) patients prescribed with tadalafil by clu...
2022, 24 November
A Natural Language Processing (NLP) Approach to Au...
Patients’ testimonials (e.g. posts on forums or responses to questionnaires) provide valuable insights to define and characterize patient-reporte...
2019, 17 September
Unmet medical needs in people with type 2 diabetes...
Limited data exist on the impact of different insulin therapy regimes on outcomes in people with diabetes. The current study describes the unmet me...
2018, 03 October
A machine learning algorithm can identify clusters...
Detecting consistent patterns of interest can be performed using data-driven subgroup discovery algorithms. These may be instrumental in exploiting...