In East Asia, nearly 50% of lung cancer patients are never-smokers, underscoring a disease pattern often driven by other factors such as genetic or familial predisposition rather than tobacco exposure.1 However, efforts to implement effective screening strategies for never-smokers have been challeng

Stroke is one of the leading causes of long-term disability worldwide, and effective post-stroke rehabilitation plays a critical role in improving functional outcomes and quality of life for survivors.1 Yet, conventional in-person rehabilitation faces numerous challenges, including therapist shortag

In the treatment of coronary artery disease (CAD), fractional flow reserve (FFR) can be performed during coronary angiography to evaluate the need for percutaneous coronary intervention (PCI).1 Nevertheless, the efficacy of wire-based FFR is constrained by its practical limitations.1,2 Computational

It is projected that there will be 1.9 million new cancer diagnoses and over 600,000 cancer deaths in 2022 in the United States alone.¹ Spine is the most common site for bone metastasis; up to 70% of cancer patients could experience spinal metastasis (SM) and about 20% of them become symptomatic, causing considerable pain and morbidity.² Most common regions for SM are dorsal (45%), lumbar (17%), cervical (14%), and dorsolumbar (10%).³ Vertebral fractures (VFs) are the common complications of SM, with an estimation of 30% of patients developing VFs that mostly require surgery.⁴ Tumor lesions and some treatments for cancer can lead to loss of bone tissue, thus increasing the risk of VFs.⁵ Hence, it is imperative to predict the VF risk in SM patients, so that well-informed interventions can be designed.⁵ Factors influencing VFs include both the macro- and micro-structure of the vertebra, especially of the trabecula.⁵ In-vitro methods are used to study the biomechanical forces that alter the vertebral shape, but they cannot accurately measure in-vivo stresses that damage its microstructure.⁵ The development of computational modeling has made it a compelling tool for measuring these in-vivo stressors.⁵ A recent study by Ahmadian et al was to assess the feasibility of the artificial intelligence (AI)-assisted framework to create ‘digital twins’ of the human vertebra, termed ReconGAN, to predict the VF risk in both osteolytic and osteoblastic metastatic tumors.⁵

During COVID-19, digital health has become increasingly more prevalent over the world. Composed of information and communications technology, computer sciences, genomics, artificial intelligence (AI) and more, digital health helps collect patients’ information and analyze a large amount of data to s