LEADER 03728namaa2200829uu 4500
001 doab93218
003 oapen
005 20221025
006 m o d
007 cr|mn|---annan
008 221025s2022 xx |||||o ||| 0|eng d
020 |a 9783036552552 
020 |a 9783036552569 
020 |a books978-3-0365-5256-9 
024 7 |a 10.3390/books978-3-0365-5256-9  |2 doi 
040 |a oapen  |c oapen 
041 0 |a eng 
042 |a dc 
072 7 |a MBN  |2 bicssc 
720 1 |a Ramo-Tello, Cristina M.  |4 edt 
720 1 |a Ramo-Tello, Cristina M.  |4 oth 
245 0 0 |a Personalized Diagnosis and Therapy for Multiple Sclerosis 
260 |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2022 
300 |a 1 online resource (124 p.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
506 0 |a Open Access  |f Unrestricted online access  |2 star 
520 |a We all agree that people with MS need to be cared in a profoundly personalized way. The care of the patient with MS is still based on the presence of relapses, so their successful diagnosis and treatment is fundamental and will condition the therapeutic strategies to follow with the patient. The treatment strategies are a highly controversial topic of debate that is increasingly supported by robust objective biological markers of response and that also increasingly take into account the dynamics and predictors of cognitive impairment along the disease course, which includes the adoption of new trends in the field of machine learning techniques. However, we all know that patient care goes beyond being treated with drugs and we cannot overlook reminding patients of the importance of their lifestyle behaviors that vary according to the MS phenotype, in order to improve their quality of life. Teleconsultation is a new care strategy proved to be feasible and well-received by patients with MS that will undoubtedly become reinforced because it will allow a closer follow-up of the patient without the need for displacement. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/4.0/  |2 cc  |u https://creativecommons.org/licenses/by/4.0/ 
546 |a English 
650 7 |a Public health and preventive medicine  |2 bicssc 
653 |a artificial intelligence 
653 |a biomarker 
653 |a CD49d 
653 |a cognition 
653 |a cognitive impairment 
653 |a digital health 
653 |a diseases modifying therapies 
653 |a early intense therapy 
653 |a escalating strategy 
653 |a extended interval dose 
653 |a feasibility 
653 |a he-DMT 
653 |a health-related quality of life 
653 |a immunomonitoring 
653 |a internet 
653 |a lifestyle behavior 
653 |a longitudinal 
653 |a machine learning 
653 |a methylprednisolone 
653 |a mood 
653 |a MS management 
653 |a MS phenotype 
653 |a multiple sclerosis 
653 |a multiple sclerosis treatment 
653 |a n/a 
653 |a natalizumab 
653 |a neuroimaging 
653 |a neuromyelitis optica spectrum disorder 
653 |a personalized dose 
653 |a predictors 
653 |a prognosis 
653 |a pseudo-relapses 
653 |a quality of life 
653 |a relapse 
653 |a sVCAM-1 
653 |a teleconsultation 
653 |a treatment algorithm 
793 0 |a DOAB Library. 
856 4 0 |u https://directory.doabooks.org/handle/20.500.12854/93218  |7 0  |z Open Access: DOAB: description of the publication 
856 4 0 |u https://mdpi.com/books/pdfview/book/6116  |7 0  |z Open Access: DOAB, download the publication