Results 141 to 150 of about 142,938 (289)

Enhancing Heart Disease Prediction Using CardiAI: With Key Performance Metrics Accuracy, Precision, Recall and F1-Score

International Journal of Intelligent Systems and Applications in Engineering
In this study, we introduce CardiAI, a pioneering deep learning algorithm meticulously crafted for precise heart disease prediction. Unlike existing models, CardiAI's innovation lies in its intricate architecture, integrating strategic dropout layers, early stopping mechanisms, and sophisticated techniques to mitigate overfitting.
Mulaguri, Asish Tony, Katta, Sai Krishna, Karanam, Venkata Kousik, Pachipala, Yellamma, Narisety, Sriyaa   +4 more
openaire   +1 more source

Nap1L4a Cooperates with Scl/Klf1 to Recruit H2A.Z in Mediating Interactions Among Cis‐Regulatory Elements and Transcription Required for Primitive Erythropoiesis in Zebrafish

Advanced Science, EarlyView.
Nap1l4a is required in erythropoiesis and hypoxia responses via physical interaction with Klf1 and Scl to recruit the histone variant H2A.Z. This facilitates its associated cis‐regulatory element (CRE) remodeling and the consequent chromatin assembly, and activates the transcription of erythroid lineage‐specific genes.
JiaHao Shi, FuMing Lai, Zheng Shen, XiaoYan Zhang, HanFei Wang, WenYe Liu, YunLong Wang, KuanYu Li, GuoLiang Li, YaPing Fang, Jing‐Xia Liu   +10 more
wiley   +1 more source

Piscis: a novel loss estimator of the F1 score enables accurate spot detection in fluorescence microscopy images via deep learning

AbstractSingle-molecule RNA fluorescencein situhybridization (RNA FISH)-based spatial transcriptomics methods have enabled the accurate quantification of gene expression at single-cell resolution by visualizing transcripts as diffraction-limited spots.
Zijian Niu, Aoife O’Farrell, Jingxin Li, Sam Reffsin, Naveen Jain, Ian Dardani, Yogesh Goyal, Arjun Raj   +7 more
openaire   +2 more sources

Connexin 26 Functions as a Direct Transcriptional Regulator During the Cochlea Development

Advanced Science, EarlyView.
Connexin26 can not only form intercellular channels that mediate rapid communication on the cell membrane, but also enter the nucleus as a transcription factor to directly regulate the transcription of nuclear genes. In the developing cochlea, Cx26 can control the maturation of the molecular scissor ADAM10 by regulating the transcription of TspanC8 ...
Xiaozhou Liu, Le Xie, Yuan Jin, Sen Chen, Xinyu Shi, Yanjun Zong, Zhengdong Zhao, Wei‐Jia Kong, Yu Sun   +8 more
wiley   +1 more source

SMENN-hybrid: an efficient technique combining the synthetic minority oversampling technique with ensemble learning for diabetes prediction. [PDF]

Sci Rep
Houssein EH, Ibrahim IA, Mostafa A, Albarrak AM, Younan M.   +4 more
europepmc   +1 more source

Detail of precision, recall, accuracy and F1 Score for pre-trained Naïve Bayes on Bug Dataset.

Sajid Ullah (8299908), M. Irfan Uddin (8909933), Muhammad Adnan (678952), Ala Abdulsalam Alarood (21526803), Abdulkream Alsulami (21526806), Safa Habibullah (21526809)   +5 more
openalex   +1 more source

The Evolutionarily Conserved TPM1 Super‐Enhancer Drives Skeletal Muscle Regeneration via Mechanotransduction Signaling

Advanced Science, EarlyView.
By integrating biomechanical and epigenetic cues, the evolutionarily conserved TPM1 super‐enhancer drives myogenesis via TEAD4‐mediated chromatin looping. This mechanism produces species‐specific outputs (linear TPM1 mRNA in mice and CircTPM1 in bovine) that activate PI3K/AKT mechanotransduction and the MYH10/MYL3 axis to execute cytoskeletal ...
Ruimen Zhang, Wanyou Feng, Yanyan Yang, Yu Pan, Chaoxia Zou, Leyi Wang, Sanbao Zhang, Yimin Zhao, Yongmei Wu, Jinling Wang, Jianwei Zou, Kehe Cen, Yongwang Zhang, Han Huang, Yurong Xu, Li Zhong, Hailong Gong, Juanru Cheng, Jingyuan Liang, Zihua Zheng, Qinyang Jiang, Jingwei Wei, Hui Li, Minhui Liang, Deshun Shi, Sufang Yang, Yanfei Deng, Yingming Wei   +27 more
wiley   +1 more source

Visual Food Ingredient Prediction Using Deep Learning with Direct F-Score Optimization. [PDF]

Foods
Theera-Ampornpunt N, Treepong P.
europepmc   +1 more source

Comparison of Proposed Model, RF, SVM, DNN, and RNN models using F1 Score for Class 1 on imbalanced datasets.

Saim Chishti (22272188), Faryal Nosheen (22272191), Joddat Fatima (22272194), Nadia Sultan (11268617), Madiha Khalid (10196725)   +4 more
openalex   +1 more source