Background Asymptomatic and high-risk COVID-19 patients are advised to self-isolate at home. However, patients may not realize that the condition is deteriorating until too late. Objective This study aims to review various artificial intelligence-based telemedicine research during the COVID-19 outbreak and proposes a framework for developing telemedicine powered by artificial intelligence to monitor progression in COVID-19 patients during isolation at home. It also aims to map challenges using artificial intelligence-based telemedicine in the community. Methods A systematic review was performed for the related articles published in 2019–2021 and conducted in the PubMed and ScienceDirect database using the keywords “telemedicine,” “artificial intelligence,” and “COVID-19”. The inclusion criteria were full-text articles and original research written in the English language. Results Thirteen articles were included in this review to describe the current application of artificial intelligence-based telemedicine during the COVID-19 pandemic. Various current applications have been implemented, such as for early diagnosis and tracing of contact for the users, to monitor symptoms and decision-making treatment, clinical management, and virtual and remote treatment. We also proposed the framework of telemedicine powered by artificial intelligence for support the self-isolation of COVID-19 patients based on the recent update in technology. However, we identified some challenges for using digital health technologies because of the ethical and practical use, the policy and regulation, and device use both for healthcare workers and patients. Conclusion Artificial intelligence promises to improve the practice of medicine in various ways. However, practical applications still need to be explored, and medical professionals also need to adapt to these advances for better healthcare delivery to the public.
Diabetes mellitus tipe 2 disebabkan oleh ekspresi PTP1B yang tinggi dan mempengaruhi aktivitas PTKs, yang menyebabkan insulin gagal berikatan dengan reseptor insulin dan menginduksi resistensi insulin. Senyawa xanton dan benzofenon merupakan senyawa yang telah diketahui memiliki aktivitas farmakologi sebagai antidiabetes. Salah satu tanaman dengan kandungan senyawa tersebut adalah Garcinia cowa. Penelitian ini dilakukan dengan tujuan untuk mengetahui afinitas dan mekanisme inhibisi PTP1B oleh senyawa turunan xanton, benzofeno, dan triterpenoid dalam Garcinia cowa antara lain garcinia cowone K, guttiferone I, 1,7-dihydroxyxanthone, 1-hydroxyl-7-methoxyxanthone, mangostinone, ?-mangostin, cowanol, gacibiphenyl C, friedelin, ?-friedelinol, dan oleanane-12-ol secara in silico dengan molecular docking serta melakukan studi pre-ADMET terhadap senyawa tersebut. Molecular docking dilakukan melalui beberapa tahap diantaranya preparasi dan optimasi struktur 3D senyawa uji, preparasi struktur 3D reseptor PTP1B, validasi metode, dan docking senyawa uji dengan PTP1B. Hasil yang diperoleh dari docking senyawa uji dengan reseptor PTP1B berupa energi ikatan, konstanta inhibisi (KI), dan ikatan hidrogen. Semakin rendah nilai energi ikatan menunjukkan ikatan antara protein dan ligan yang dihasilkan semakin stabil. Hasil penelitian menunjukkan energi ikatan dan KI PTP1B dengan native ligand berturut-turut sebesar -10,07 kkal/mol dan 0,0417 ?M. Sementara dengan senyawa ?-mangostin berturut-turut sebesar -8,91 kkal/mol dan 0.29317 ?M. Hal tersebut menunjukkan bahwa senyawa ?-mangostin memiliki potensi sebagai antidiabetes mellitus tipe 2 dengan menghambat PTP1B. Selain itu, senyawa ?-mangostin juga memiliki profil ADMET yang baik. Kata kunci: antidiabetes, diabetes mellitus tipe 2, penambatan molekuler, PTP1B, Xanton Type 2 diabetes mellitus is caused by high PTP1B expression and affects the activity of PTKs, which causes insulin to fail to bind to insulin receptors, and induces insulin resistance. Xanthones and benzophenones are compounds that have been known to have pharmacological activity as antidiabetic. One of the plants containing these compounds is Garcinia cowa. This study aims to know the affinity and inhibition mechanism of PTP1B by xanthones, benzophenones, and triterpenoid in Garcinia cowa, including garcinia cowone K, guttiferone I, 1,7-dihydroxyxanthone, 1-hydroxyl-7 methoxyxanthone, mangostinone, ?-mangostin, cowanol, gacibiphenyl C, friedelin, ?-friedelinol, and oleanane-12-ol in silico by molecular docking and conducted a pre-ADMET study of these compounds. Molecular docking is carried out in several steps including preparation and optimization of the 3D structure of the compound, preparation of the PTP1B receptor 3D structure, method validation, and docking of the compound with PTP1B. The results obtained from the docking of the compound with the PTP1B receptor appears in the form of bond energies, inhibition constant (IC), and hydrogen bonds. The lower the bond energy value, the more stable the bond between the protein and the resulting ligand is. The results showed that the bond energy and IC value of PTP1B with the native ligand is -10,07 kcal/mol and 0,0417 ?M. Meanwhile the ?-mangostin compound is -8,91 kcal/mol and 0,29317 ?M. It shows that the ?-mangostin has potential as an antidiabetic mellitus type 2 agent by inhibiting PTP1B. In addition, ?-mangostin also shows a good ADMET profile. Keywords: antidiabetic, molecular docking, PTP1B, type 2 diabetes mellitus, xanthones
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