RESULTS: This study found that the annual rate of deforestation within inland forests in Peninsular Malaysia was 0.38% year-1 and subsequently caused a carbon loss of approximately 9 million Mg C year-1, which is equal to emissions of 33 million Mg CO2 year-1, within the ten-year observation period. Spatially explicit maps of AGB over the dipterocarps forests in the entire Peninsular Malaysia were produced. The RMSE associated with the AGB estimation was approximately 117 Mg ha-1, which is equal to an error of 29.3% and thus an accuracy of approximately 70.7%.
CONCLUSION: The PALSAR and PALSAR-2 systems offer a great opportunity for providing consistent data acquisition, cloud-free images and wall-to-wall coverage for monitoring since at least the past decade. We recommend the proposed method and findings of this study be considered for MRV in REDD+ implementation in Malaysia.
METHODS: This is a single-center retrospective observational study of patients with malignant biliary obstruction undergoing EUS-HGS after failed ERCP between January 2018 and May 2019. The end-point of the study was to assess the technical and clinical success rate, as well as the stent- and procedure-related complications.
RESULTS: There were 20 subjects in this study. The average age was 71.8 ± 7.6 years. Most patients were male, 16 (80%). Inaccessible papillae was the most common indication for this procedure, 16 (80%). Technical success was achieved in all patients. The average procedural time was 39.9 ± 1.3 min. Mean preprocedural bilirubin levels were 348.6 ± 28.8 and subsequently decreased to 108.94 ± 37.1 μmol/L at 2 weeks postprocedure. The clinical success rate was 95% (19/20), with one patient requiring percutaneous transhepatic biliary drainage (PTBD). There were no stent- or procedure-related complications reported in this study.
CONCLUSION: EUS-HGS with PCMS is a feasible, effective, and safe alternative for biliary decompression in patients with failed endoscopic retrograde cholangiopancreatography (ERCP).
OBJECTIVE: This research aims to provide a literature review study and an in-depth analysis to (1) investigate the procedure and roles of remote diagnosis in telemedicine; (2) review the technical tools and technologies used in remote diagnosis; (3) review the diseases diagnosed remotely in telemedicine; (4) compose a crossover taxonomy among diseases, technologies, and telemedicine; (5) present lists of input variables, vital signs, data and output decisions already applied in remote diagnosis; (6) Summarize the performance assessment measures utilized to assess and validate remote diagnosis models; and (7) identify and categorize open research issues while providing recommendations for future advancements in intelligent remote diagnosis within telemedicine systems.
METHODS: A systematic search was conducted using online libraries for articles published from 1 January 2016 to 13 September 2023 in IEEE, PubMed, Science Direct, Springer, and Web of Science. Notably, searches were limited to articles in the English language. The papers examine remote diagnosis in telemedicine, the technologies employed for this function, and the ramifications of diagnosing patients outside hospital settings. Each selected study was synthesized to furnish proof about the implementation of remote diagnostics in telemedicine.
RESULTS: A new crossover taxonomy between the most important diagnosed diseases and technologies used for this purpose and their relationship with telemedicine tiers is proposed. The functions executed at each tier are elucidated. Additionally, a compilation of diagnostic technologies is provided. Additionally, open research difficulties, advantages of remote diagnosis in telemedicine, and suggestions for future research prospects that require attention are systematically organized and presented.
CONCLUSIONS: This study reviews the role of remote diagnosis in telemedicine, with a focus on key technologies and current approaches. This study highlights research challenges, provides recommendations for future directions, and addresses research gaps and limitations to provide a clear vision of remote diagnosis in telemedicine. This study emphasizes the advantages of existing research and opens the possibility for new directions and smart healthcare solutions.