New Cognitive Deep-Learning CAPTCHA.
CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart), or HIP (Human Interactive Proof), has long been utilized to avoid bots manipulating web services. Over the years, ...
ARN : Questions médicales fréquentes
Sous-catégories
66 au total
└─
ARN circulaire
RNA, CircularD000079962 -
D13.444.735.032
└─
Isoformes d'ARN
RNA IsoformsD059368 -
D13.444.735.064
└─
ARN des algues
RNA, AlgalD048030 -
D13.444.735.130
└─
ARN des archées
RNA, ArchaealD019642 -
D13.444.735.300
└─
ARN bactérien
RNA, BacterialD012329 -
D13.444.735.473
└─
ARN fongique
RNA, FungalD012331 -
D13.444.735.500
└─
ARN des helminthes
RNA, HelminthD018510 -
D13.444.735.520
└─
ARN messager
RNA, MessengerD012333 -
D13.444.735.544
└─
ARN mitochondrial
RNA, MitochondrialD000077278 -
D13.444.735.580
└─
ARN tumoral
RNA, NeoplasmD012334 -
D13.444.735.615
└─
ARN nucléaire
RNA, NuclearD015138 -
D13.444.735.628
└─
ARN des plantes
RNA, PlantD018749 -
D13.444.735.635
└─
Précurseurs des ARN
RNA PrecursorsD012322 -
D13.444.735.640
└─
ARN des protozoaires
RNA, ProtozoanD016053 -
D13.444.735.650
└─
ARN ribosomique
RNA, RibosomalD012335 -
D13.444.735.686
└─
ARN satellite
RNA, SatelliteD019244 -
D13.444.735.721
└─
ARN de transfert
RNA, TransferD012343 -
D13.444.735.757
└─
ARN non traduit
RNA, UntranslatedD022661 -
D13.444.735.790
└─
ARN viral
RNA, ViralD012367 -
D13.444.735.828
└─└─
ARN messager stocké
RNA, Messenger, StoredD023121 -
D13.444.735.544.527
└─└─
ARN nucléaire hétérogène
RNA, Heterogeneous NuclearD012332 -
D13.444.735.628.806
└─└─
ARN des chloroplastes
RNA, ChloroplastD018747 -
D13.444.735.635.575
└─└─
ARN ribosomique 5S
RNA, Ribosomal, 5SD012341 -
D13.444.735.686.650
└─└─
ARN ribosomique 5.8S
RNA, Ribosomal, 5.8SD012340 -
D13.444.735.686.660
└─└─
ARN ribosomique 16S
RNA, Ribosomal, 16SD012336 -
D13.444.735.686.670
└─└─
ARN ribosomique 18S
RNA, Ribosomal, 18SD012337 -
D13.444.735.686.675
└─└─
ARN ribosomique 23S
RNA, Ribosomal, 23SD012338 -
D13.444.735.686.680
└─└─
ARN ribosomique 28S
RNA, Ribosomal, 28SD012339 -
D13.444.735.686.690
└─└─
Introns autoépissables d'ARN ribosomique
RNA, Ribosomal, Self-SplicingD044563 -
D13.444.735.686.845
└─└─
Satellite du virus de la mosaïque du concombre
Cucumber Mosaic Virus SatelliteD019401 -
D13.444.735.721.250
└─└─
ARN de transfert spécifiques des différents acides aminés
RNA, Transfer, Amino Acid-SpecificD012345 -
D13.444.735.757.700
└─└─
ARN de transfert aminoacylés
RNA, Transfer, Amino AcylD012346 -
D13.444.735.757.715
└─└─
ARN catalytique
RNA, CatalyticD016337 -
D13.444.735.790.199
└─└─
ARN long non codant
RNA, Long NoncodingD062085 -
D13.444.735.790.375
└─└─
Petit ARN non traduit
RNA, Small UntranslatedD058727 -
D13.444.735.790.552
└─└─
ARN subgénomique
Subgenomic RNAD000094762 -
D13.444.735.828.500
└─└─└─
ARN de transfert de l'alanine
RNA, Transfer, AlaD012344 -
D13.444.735.757.700.050
└─└─└─
ARN de transfert de l'arginine
RNA, Transfer, ArgD012347 -
D13.444.735.757.700.075
└─└─└─
ARN de transfert de l'asparagine
RNA, Transfer, AsnD012348 -
D13.444.735.757.700.085
└─└─└─
ARN de transfert de l'acide aspartique
RNA, Transfer, AspD012349 -
D13.444.735.757.700.090
└─└─└─
ARN de transfert de la cystéine
RNA, Transfer, CysD012350 -
D13.444.735.757.700.200
└─└─└─
ARN de transfert de la glutamine
RNA, Transfer, GlnD012351 -
D13.444.735.757.700.400
└─└─└─
ARN de transfert de l'acide glutamique
RNA, Transfer, GluD012352 -
D13.444.735.757.700.410
└─└─└─
ARN de transfert de la glycine
RNA, Transfer, GlyD012353 -
D13.444.735.757.700.420
└─└─└─
ARN de transfert de l'histidine
RNA, Transfer, HisD012354 -
D13.444.735.757.700.450
└─└─└─
ARN de transfert de l'isoleucine
RNA, Transfer, IleD012355 -
D13.444.735.757.700.480
└─└─└─
ARN de transfert de la leucine
RNA, Transfer, LeuD012356 -
D13.444.735.757.700.500
└─└─└─
ARN de transfert de la lysine
RNA, Transfer, LysD012357 -
D13.444.735.757.700.510
└─└─└─
ARN de transfert de la méthionine
RNA, Transfer, MetD012358 -
D13.444.735.757.700.525
└─└─└─
ARN de transfert de la phénylalanine
RNA, Transfer, PheD012360 -
D13.444.735.757.700.650
└─└─└─
ARN de transfert de la proline
RNA, Transfer, ProD012361 -
D13.444.735.757.700.660
└─└─└─
ARN de transfert de la sérine
RNA, Transfer, SerD012362 -
D13.444.735.757.700.700
└─└─└─
ARN de transfert de la thréonine
RNA, Transfer, ThrD012363 -
D13.444.735.757.700.725
└─└─└─
ARN de transfert du tryptophane
RNA, Transfer, TrpD012364 -
D13.444.735.757.700.740
└─└─└─
ARN de transfert de la tyrosine
RNA, Transfer, TyrD012365 -
D13.444.735.757.700.750
└─└─└─
ARN de transfert de la valine
RNA, Transfer, ValD012366 -
D13.444.735.757.700.900
└─└─└─
microARN
MicroRNAsD035683 -
D13.444.735.790.552.500
└─└─└─
Systèmes CRISPR-Cas, ARN, guide
RNA, Guide, CRISPR-Cas SystemsD000094704 -
D13.444.735.790.552.563
└─└─└─
ARN guide
RNA, Guide, KinetoplastidaD017394 -
D13.444.735.790.552.625
└─└─└─
Petit ARN cytoplasmique
RNA, Small CytoplasmicD020733 -
D13.444.735.790.552.750
└─└─└─
Petit ARN interférent
RNA, Small InterferingD034741 -
D13.444.735.790.552.875
└─└─└─
Petit ARN nucléaire
RNA, Small NuclearD012342 -
D13.444.735.790.552.937
└─└─└─
ARN de tête épissé
RNA, Spliced LeaderD020038 -
D13.444.735.790.552.968
└─└─└─└─
MicroARN circulant
Circulating MicroRNAD000074166 -
D13.444.735.790.552.500.500
└─└─└─└─
ARN interagissant avec Piwi
Piwi-Interacting RNAD000094322 -
D13.444.735.790.552.875.500
└─└─└─└─
Petit ARN nucléolaire
RNA, Small NucleolarD020537 -
D13.444.735.790.552.937.800
Sources (10000 au total)
Applications of Deep Learning in Endocrine Neoplasms.
Machine learning methods have been growing in prominence across all areas of medicine. In pathology, recent advances in deep learning (DL) have enabled computational analysis of histological samples, ...
Deep learning in acute vertigo diagnosis.
Recent advances in artificial intelligence are transforming healthcare and there are increasing efforts to apply these breakthroughs to the diagnosis of acute vertigo. Because the diagnosis of vertigo...
Deep Learning for FAST Quality Assessment.
To determine the feasibility of using a deep learning (DL) algorithm to assess the quality of focused assessment with sonography in trauma (FAST) exams.... Our dataset consists of 441 FAST exams, classified as good-quality or poor-quality, with 3161 videos. We first used convolutional neural networks (CNNs), pretrained on the Imagenet dataset and fine-tu... The results with the encoder-classifier networks were much better than the transfer learning results with CNNs. This was primarily because the Imagenet dataset is not a good match for the ultrasound q... Using an autoencoder to compress FAST images is a very effective way to obtain features that can be used to predict exam quality. These features are more suitable than those obtained from CNNs pretrai...
Loss of plasticity in deep continual learning.
Artificial neural networks, deep-learning methods and the backpropagation algorithm...
Deep Learning Enhanced Electrochemiluminescence Microscopy.
Limited by the efficiency of electrochemiluminescence, tens of seconds of exposure time are typically required to get a high-quality image. Image enhancement of short exposure time images to obtain a ...
Artificial Intelligence and Deep Learning for Rheumatologists.
Deep learning has emerged as the leading method in machine learning, spawning a rapidly growing field of academic research and commercial applications across medicine. Deep learning could have particu...
A Review on Multiscale-Deep-Learning Applications.
In general, most of the existing convolutional neural network (CNN)-based deep-learning models suffer from spatial-information loss and inadequate feature-representation issues. This is due to their i...
Genomics enters the deep learning era.
The tremendous amount of biological sequence data available, combined with the recent methodological breakthrough in deep learning in domains such as computer vision or natural language processing, is...
Deep Learning for Infant Cry Recognition.
Recognizing why an infant cries is challenging as babies cannot communicate verbally with others to express their wishes or needs. This leads to difficulties for parents in identifying the needs and t...