Federated Contrastive Learning for Dermatological Disease Diagnosis via On-device Learning (Invited Paper)

Author(s):  
Yawen Wu ◽  
Dewen Zeng ◽  
Zhepeng Wang ◽  
Yi Sheng ◽  
Lei Yang ◽  
...  
Author(s):  
M. Shamsul Arifin ◽  
M. Golam Kibria ◽  
Adnan Firoze ◽  
M. Ashraful Amini ◽  
Hong Yan

Author(s):  
Karen K. Baker ◽  
David L. Roberts

Plant disease diagnosis is most often accomplished by examination of symptoms and observation or isolation of causal organisms. Occasionally, diseases of unknown etiology occur and are difficult or impossible to accurately diagnose by the usual means. In 1980, such a disease was observed on Agrostis palustris Huds. c.v. Toronto (creeping bentgrass) putting greens at the Butler National Golf Course in Oak Brook, IL.The wilting symptoms of the disease and the irregular nature of its spread through affected areas suggested that an infectious agent was involved. However, normal isolation procedures did not yield any organism known to infect turf grass. TEM was employed in order to aid in the possible diagnosis of the disease.Crown, root and leaf tissue of both infected and symptomless plants were fixed in cold 5% glutaraldehyde in 0.1 M phosphate buffer, post-fixed in buffered 1% osmium tetroxide, dehydrated in ethanol and embedded in a 1:1 mixture of Spurrs and epon-araldite epoxy resins.


1984 ◽  
Vol 52 (03) ◽  
pp. 250-252 ◽  
Author(s):  
Y Sultan ◽  
Ph Avner ◽  
P Maisonneuve ◽  
D Arnaud ◽  
Ch Jeanneau

SummaryTwo monoclonal antibodies raised against FVIII/von Willebrand protein were used in an immunoradiometric assay (IRMA) to measure this antigen in normal plasma and plasma of patients with different forms of von Willebrand’s disease. The first antibody, an IgG1 was used to coat polystyrene tubes, the second one, an IgG2a, iodinated and used in the second step. Both antibodies inhibit ristocetin induced platelet agglutination and react strongly with platelets, megacaryocytes and endothelial cells. The IRMA test using these antibodies showed greater sensitivity than that using rabbit polyclonal anti VIIIRAg antibodies. A good correlation between the two tests was nevertheless found when VIIIRAg was measured in the majority of patient’s plasma. However 5 patients from 3 different families showed more antigenic material in the rabbit antibody IRMA than in the monoclonal antibody IRMA. It is suggested therefore that the monoclonal antibodies identify part of the VIIIR:Ag molecule showing structural abnormalities in these vWd patients, these structural changes remaining undetected by the polyclonal antibodies.


2018 ◽  
Vol 9 (1) ◽  
pp. 8
Author(s):  
Bernardo Almeida

Snapping hip syndrome is a condition in which the predominant symptom is the snapping feelingaround the hip joint caused by a dynamic impingement between muscles or tendons and boneprominences. The etiology of the snapping hip types and consequently the therapeutic targets havebeen subjects of discussion and controversy along the years. A careful clinical history and physicalexamination is frequently enough for this disease diagnosis. Treatment is typically conservative,however when it is not successful surgical treatment is indicated, consisting on the snapping muscleor tendons lengthening. The authors review in this paper the current scientific literature about functionalanatomy, physiopathology, symptoms, diagnosis and treatment of snapping hip.


Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.


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