Results 141 to 150 of about 9,956,497 (284)

Frequency Band Analysis of Multiple Stationary Time Series. [PDF]

Stat Med
Brubaker CK, Manning JP, Yentes JM, Bruce SA.   +3 more
europepmc   +1 more source

Cutaneous Melanoma Drives Metabolic Changes in the Aged Bone Marrow Immune Microenvironment

Aging and Cancer, EarlyView.
Melanoma, the deadliest form of skin cancer, increasingly affects older adults. Our study reveals that melanoma induces changes in iron and lipid levels in the bone marrow, impacting immune cell populations and increasing susceptibility to ferroptosis.
Alexis E. Carey, Murilo Ramos Rocha, Cheyenne Palm, Vania Wang, Denys Balandin, Ethan Black, Kevin Y. Zhang, Fan Huang, Daniel J. Zabransky, Yash Chhabra, Mareike Peters, Gabriel Ghiaur, Ashani Weeraratna   +12 more
wiley   +1 more source

VIST: variational inference for single cell time series. [PDF]

Genome Biol
Xu B, Braun R.
europepmc   +1 more source

The Aging Blood: Cellular Origins, Circulating Drivers, and Therapeutic Potential

Aging and Cancer, EarlyView.
As a conduit linking all organs, the blood system both reflects and actively drives systemic aging. This review highlights how circulating pro‐aging and antiaging factors and age‐associated hematopoietic stem cell dysfunction contribute to immunosenescence and multi‐organ decline, positioning the hematopoietic system as a target for aging intervention.
Hanqing He, Jianwei Wang
wiley   +1 more source

Forecasting Tuberculosis Incidence in Somalia: A Comparative Analysis of Single and Hybrid Time-Series Models. [PDF]

Health Sci Rep
Dahir HM, Korse AH, Mohamed FI, Nadarajah S, Hassan MS.   +4 more
europepmc   +1 more source

Network Localization of Fatigue in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo, Jaakko Kungshamn, Albert Bellmunt‐Gil, Silvia Tommasin, Abhineet Ojha, Matias Viitala, Juho Aaltonen, Jyrki Lötjönen, Juha Koikkalainen, Pauli Ylikotila, Patrizia Pantano, Merja Soilu‐Hänninen, Juho Joutsa   +12 more
wiley   +1 more source

Woa-wtconv-kanformer for long term time series forecasting. [PDF]

PLoS One
Ling Ming M, Wei Min Q, Yi Fan D, Yu Ning Z.   +3 more
europepmc   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Time series dataset for network security situational awareness. [PDF]

Data Brief
Staňa R, Pekarčík P, Sokol P, Bartoš V.   +3 more
europepmc   +1 more source

Boknis Eck Time Series Station [PDF]

, 2010
Bange, Hermann W.
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