Results 181 to 190 of about 610,735 (230)

Integrating machine learning techniques for critical node identification in complex networks. [PDF]

Sci Rep
ReddyPriya M, Enduri MK, Hajarathaiah K, Satish A, Bandaru N.   +4 more
europepmc   +1 more source

Unlocking the Potential of MXene‐Based Electrochemical Biosensors: A Review of Biofunctionalization Strategies and Biosensing Principles

Advanced Materials Technologies, EarlyView.
ABSTRACT Electrochemical biosensors enable the accurate and timely detection of clinical biomarkers, improving healthcare and precision medicine. MXene nanosheets, a class of 2D transition metal carbides, nitrides, and carbonitrides, are promising materials for developing next‐generation electrochemical biosensors due to their unique physicochemical ...
Muhsin Ali, Sharat Chandra Barman, Isobel Steer, Aya H. Alshareef, Dana Alsulaiman   +4 more
wiley   +1 more source

Machine learning model for predicting improvement in left ventricular systolic function in patients with heart failure and reduced ejection fraction. [PDF]

Int J Cardiol Heart Vasc
Sepehrvand N, Gilbert C, Chunta A, Youngson E, Ezekowitz JA, Fine NM, Howlett JG, McAlister FA, Miller RJH.   +8 more
europepmc   +1 more source

Chemically Doped Conductive Polymers for Wearable Health Monitoring

Advanced Materials Technologies, EarlyView.
Among conductive polymers, poly(3,4‐ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS), polyaniline (PANI), and polypyrrole (PPy) are the most studied and applied. Chemical doping significantly boosts intrinsic conductivity and mechanical robustness.
Mengdi Zuo, Jian Song, Hong Hu, Le Zheng, Lei Zhang, Charles H. Lawrie   +5 more
wiley   +1 more source

Artificial Intelligence and Machine Learning in Audiology and Hearing Disorders: A Scoping Review with Bibliometric and Thematic Mapping (1995-2025). [PDF]

Audiol Res
Aksoy Koçak C.
europepmc   +1 more source

Microfluidic Hydroporation Platform for Effective Allogeneic CAR‐T Cell Production and Subsequent Functional Cytotoxicity Analysis

Advanced Materials Technologies, EarlyView.
The hydroporator platform employs controlled hydrodynamic deformation for efficient mRNA and CRISPR/Cas9 delivery into primary human T cells, enabling allogeneic CAR‐T cell manufacturing. It preserves cell functionality and drives potent gene editing, CAR expression, and tumor cytotoxicity, while feature‐based analysis links these functional outcomes ...
Soohyun Jeon, Sein Kim, Hyun‐Young Kim, Duck Cho, Sungsu Park, Seohyun Kim, Aram J. Chung   +6 more
wiley   +1 more source

Clinical applications of machine learning for infection assessment in diabetic foot ulcers. [PDF]

Front Physiol
Lysnychka K, Rostoka L, Burmistrova Y, Halabitska I, Petakh P, Kamyshnyi O.   +5 more
europepmc   +1 more source

Smart Closed‐Loop Systems in Personalized Healthcare: Advances and Outlook

Advanced Materials Technologies, EarlyView.
A smart closed‐loop e‐textile integrates multimodal sensing, onboard processing, wireless communication, and wearable power to enable real‐time physiological/biochemical monitoring and feedback‐controlled therapy. ABSTRACT Smart textiles represent a revolutionary frontier in healthcare, seamlessly blending fabric and advanced technologies to create ...
Safoora Khosravi, Sang Won Lee, Mohammad Abrar Uddin, Sina Hassanpoor, Neha Suvindran, Katherine Le, Harun Arkaz, Harishkumar Narayana, Saeid Soltanian, Danial Khorsandi, Negar Hosseinzadeh Kouchehbaghi, Taeil Kim, Yangzhi Zhu   +12 more
wiley   +1 more source

Predictive Value of Machine Learning for Poststroke Mortality Risk: Systematic Review and Meta-Analysis.

J Med Internet Res
Chen Y, Ou Z, Deng Y, Luo A, Li X, Yang Y, Yang Q, Wu X, Zhou M.   +8 more
europepmc   +1 more source

Efficient Machine Learning Prediction of Solvent-Dependent $$ {}^1\mathrm{H} $$ NMR Chemical Shifts in Zinc Complexes. [PDF]

J Comput Chem
Pillay JR, Ringleb M, Croy A, Zechel S, Schubert US, Gräfe S.   +5 more
europepmc   +1 more source