Academic Articles & Research Papers

Exploring the application and challenges of fNIRS technology in early detection of Parkinson’s disease

BackgroundParkinson’s disease (PD) is a prevalent neurodegenerative disorder that significantly benefits from early diagnosis for effective disease management and intervention. Despite advancements in medical technology, there remains a cri...

Application of MRI-Based Radiomics in Preoperative Prediction of NF2 Alteration in Intracranial Meningiomas

PurposeThis study aimed to investigate the feasibility of predicting NF2 mutation status based on the MR radiomic analysis in patients with intracranial meningioma.MethodsThis retrospective study included 105 patients with meningiomas, incl...

Mechanisms of the interaction between aging of the male reproductive system and obesity, and clinical management strategies (Review).

A false sense of hypoxia: Pro‑tumorigenic VHL‑HIF2α dysregulation in clear cell renal cell carcinoma (Review).

Towards a physics informed digital twin to predict cerebral blood flow and cerebral vascular regulation

Abstract Cerebral blood flow is essential for brain function and is governed by cerebral perfusion pressure and physiological mechanisms collectively referred to as cerebral vascular regulation (CVR). Direct measurement of cerebral blood fl...

Use of machine learning algorithms to determine the relationship between air pollution and cognitive impairment in Taiwan

Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This st...

Machine learning and applications in microbiology

To understand the intricacies of microorganisms at the molecular level requires making sense of copious volumes of data such that it may now be humanly impossible to detect insightful data patterns without an artificial intelligence applica...

Machine learning and medical education

Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and othe...

Machine Learning in Enzyme Engineering

Abstract Enzyme engineering plays a central role in developing efficient biocatalysts for biotechnology, biomedicine, and life sciences. Apart from classical rational design and directed evolution approaches, machine learning methods have b...

Introduction to Machine Learning, Neural Networks, and Deep Learning.

Purpose: To present an overview of current machine learning methods and their use in medical research, focusing on select machine learning techniques, best practices, and deep learning. Methods: A systematic literature search in PubMed was ...

Machine learning for real-time aggregated prediction of hospital admission for emergency patients

Abstract Machine learning for hospital operations is under-studied. We present a prediction pipeline that uses live electronic health-records for patients in a UK teaching hospital’s emergency department (ED) to generate short-term, probabi...

Applications of Machine Learning in Cancer Prediction and Prognosis

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, ...

Machine Learning in Medicine

Interview with Dr. Isaac Kohane on machine learning in medicine. (16:31)Download In this view of the future of medicine, patient–provider interactions are informed and supported by massive amounts of data from interactions with similar pati...

How Machine Learning Will Transform Biomedicine

Machine Learning in Medicine

Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular va...

Machine Learning and the Profession of Medicine

This Viewpoint discusses the opportunities and ethical implications of using machine learning technologies, which can rapidly collect and learn from large amounts of personal data, to provide individalized patient care....

Midbrain endocannabinoids actuate dopamine-based action selection

Summary: Quickly adapting behavior to changing environments is key for survival. Brain dopamine signals reinforce actions that procure rewards and avoid adverse outcomes. However, the molecular mechanisms within the circuits that actuate th...

Using generalized random forests to characterize vulnerability to adverse health outcomes following wildfire smoke exposure in California

Background: As the health burden attributable to wildfire activity increases under climate change, it is crucial to determine which subgroups face heightened vulnerability to wildfire smoke. Marginalized communities may experience dispropor...

Machine Learning in Radiation Oncology

Integrated Bioinformatics Analysis and Experimental Verification of Immune Cell Infiltration and the Related Core Genes in Ulcerative Colitis

Danya Zhao,1 Danping Qin,2 Liming Yin,3 Qiang Yang4 1The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 2Department of Gastroenterology, The First Affiliated Hospital of Zheji...