Results 211 to 220 of about 7,660,462 (281)

Multi‐Site Transfer Classification of Major Depressive Disorder: An fMRI Study in 3335 Subjects

Advanced Science, EarlyView.
The study proposes graph convolution network with sparse pooling to learn the hierarchical features of brain graph for MDD classification. Experiment is done on multi‐site fMRI samples (3335 subjects, the largest functional dataset of MDD to date) and transfer learning is applied, achieving an average accuracy of 70.14%.
Jianpo Su, Jian Qin, Hui Shen, Ling‐Li Zeng, Baojuan Li, Jin Liu, Xuemei Song, Li Liu, Weidan Pu, Tongjian Bai, Huaning Wang, Hong Yin, Kai Wang, Lingjiang Li, Dewen Hu   +14 more
wiley   +1 more source

Advancing neuroengineering with Neuromorphic Twins. [PDF]

Nat Commun
Chiappalone M, Levi T.
europepmc   +1 more source

Engineered Living Systems With Self‐Organizing Neural Networks: From Anatomy to Behavior and Gene Expression

Advanced Science, EarlyView.
Ectodermal tissue excised from Xenopus embryos self‐organizes into a three‐dimensional mucociliary organoid. Here, we generate a neural variant, termed neurobot, by implanting neural precursor cells. Neurobots develop mature neurons, adopt distinct morphologies, exhibit more complex motility, and respond differentially to neuroactive compounds. Imaging
Haleh Fotowat, Laurie O'Neill, Léo Pio‐Lopez, Megan M. Sperry, Patrick Erickson, Tiffany Lin, Michael Levin   +6 more
wiley   +1 more source

Compute-in-memory implementation of state space models for event sequence processing. [PDF]

Nat Commun
Zhang X, Hu M, Lu S, Kim S, Lee EY, Liu Y, Lu WD.   +6 more
europepmc   +1 more source

Foundation Model‐Enabled Multimodal Deep Learning for Prognostic Prediction in Colorectal Cancer with Incomplete Modalities: A Multi‐Institutional Retrospective Study

Advanced Science, EarlyView.
FLARE, a multimodal AI framework, combines pathology slides, radiology scans, and clinical reports to predict colorectal cancer outcomes, even when some tests are missing. Evaluated retrospectively in 1679 patients from four medical centers, it consistently achieved the best prognostic accuracy and clearly separated high‐ and low‐risk groups.
Linhao Qu, Chengsheng Zhang, Yingyong Hou, Feng Tang, Weiqi Sheng, Dan Huang, Zhijian Song   +6 more
wiley   +1 more source

Digitalizing Uganda's health supply chain system through an integrated solar-powered infrastructure at hard-to-reach health facilities. [PDF]

BMC Health Serv Res
Nakade S, Okidi D, Emiku J, Miti J, Wasswa J, Odal M, Abila R, Nshabaruhanga A, Kirunda A, Oteba M, Mugabi E, Plummer B, Christofi N, Muhumuza S, Mbaka P, Ajulong M, Lugada E.   +16 more
europepmc   +1 more source

XIAP Stabilizes DDRGK1 to Promote ER‐Phagy and Protects Against Noise‐Induced Hearing Loss

Advanced Science, EarlyView.
Mechanism of GAS‐mediated protection against noise‐induced hearing loss (NIHL). Noise exposure activates the ATF4/eIF2α axis, downregulating XIAP and promoting DDRGK1 degradation, thereby inhibiting ER‐phagy and leading to hair cell (HC) death. GAS treatment rescues XIAP and DDRGK1 expression, reactivating ER‐phagy to mitigate HC loss, synaptic damage,
Lin Yan, Yuhua Zhang, Jiawei Du, Yongjun Zhu, Wei Cao, Yongjie Wei, Han Wu, Shiyu Qiu, Shiyi Pan, Lian Chen, Pingping Liang, Renjie Chai, Jianming Yang, Qiaojun Fang   +13 more
wiley   +1 more source

Advancing Dry Electroencephalography With Scalable, Soft, and Transcranial Magnetic Stimulation‐Compatible Ti3C2Tx MXene Electrodes for Research and Clinical‐Grade Applications

Advanced Science, EarlyView.
Dry soft Ti3C2Tx MXene electroencephalography (EEG) electrodes provide low impedance (2.1 ± 1.8 kΩ at 10 Hz), long‐term stability, and enable safe simultaneous EEG and transcranial magnetic stimulation (TMS). Across scalp sites, hair types, and recording paradigms, including steady state visual evoked potentials (SSVEP), clinical EEG, and mobile EEG ...
Sneha Shankar, Jakob Michiels, Ksenija Tasich, Ashley Koluda, Ryan Rich, Brian Erickson, Eugenia Angelopoulos, Francesca Cimino, Daryl Hurwitz, Raghav Garg, Spencer R. Averbeck, Doris Xu, Mariam Josyula, Nina Petillo, James J. Gugger, Kathryn A. Davis, John Medaglia, Flavia Vitale   +17 more
wiley   +1 more source

Hardware-Oriented Approximations of Softmax and RMSNorm for Efficient Transformer Inference. [PDF]

Micromachines (Basel)
Kang Y, Wang D.
europepmc   +1 more source

Towards the transformation of MATLAB models into FPGA-Based hardware accelerators. [PDF]

Sci Rep
Bal S.
europepmc   +1 more source