Revolutionizing healthcare: the role of artificial intelligence in clinical practice

SA Alowais, SS Alghamdi, N Alsuhebany… - BMC medical …, 2023 - Springer
Introduction Healthcare systems are complex and challenging for all stakeholders, but
artificial intelligence (AI) has transformed various fields, including healthcare, with the …

Early detection of cancer

D Crosby, S Bhatia, KM Brindle, LM Coussens, C Dive… - Science, 2022 - science.org
Survival improves when cancer is detected early. However,~ 50% of cancers are at an
advanced stage when diagnosed. Early detection of cancer or precancerous change allows …

Capabilities of gpt-4 on medical challenge problems

H Nori, N King, SM McKinney, D Carignan… - arXiv preprint arXiv …, 2023 - arxiv.org
Large language models (LLMs) have demonstrated remarkable capabilities in natural
language understanding and generation across various domains, including medicine. We …

Towards generalist biomedical AI

T Tu, S Azizi, D Driess, M Schaekermann, M Amin… - NEJM AI, 2024 - ai.nejm.org
Background Medicine is inherently multimodal, requiring the simultaneous interpretation
and integration of insights between many data modalities spanning text, imaging, genomics …

AI in health and medicine

P Rajpurkar, E Chen, O Banerjee, EJ Topol - Nature medicine, 2022 - nature.com
Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the
experiences of both clinicians and patients. We discuss key findings from a 2-year weekly …

From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment

K Swanson, E Wu, A Zhang, AA Alizadeh, J Zou - Cell, 2023 - cell.com
Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

Shifting machine learning for healthcare from development to deployment and from models to data

A Zhang, L Xing, J Zou, JC Wu - Nature Biomedical Engineering, 2022 - nature.com
In the past decade, the application of machine learning (ML) to healthcare has helped drive
the automation of physician tasks as well as enhancements in clinical capabilities and …

Predicting cancer outcomes with radiomics and artificial intelligence in radiology

K Bera, N Braman, A Gupta, V Velcheti… - Nature reviews Clinical …, 2022 - nature.com
The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …

Training spiking neural networks using lessons from deep learning

JK Eshraghian, M Ward, EO Neftci… - Proceedings of the …, 2023 - ieeexplore.ieee.org
The brain is the perfect place to look for inspiration to develop more efficient neural
networks. The inner workings of our synapses and neurons provide a glimpse at what the …

Oral squamous cell carcinomas: state of the field and emerging directions

Y Tan, Z Wang, M Xu, B Li, Z Huang, S Qin… - International journal of …, 2023 - nature.com
Oral squamous cell carcinoma (OSCC) develops on the mucosal epithelium of the oral
cavity. It accounts for approximately 90% of oral malignancies and impairs appearance …