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| 1 | Direct laser deposition of alloys from elemental powder blends显示文摘 | SCHWENDNER K I BANERJEE R COLLINS P C | 2001 | Scripta Materialia2001，45，10： | 1 |
| 2 | Direct laser deposition of alloys from elemental powder blends 显示文摘 | Schwendner K I Banel liee R Collins P C | 2001 | Scripta Materialia2001，45，： | 1 |
| 3 | Direct laser deposition of alloys from elemental powder blends显示文摘 | SCHWENDNER K I BANERJEE R COLLINS P C | 2001 | Scripta Materialia2001，45，： | 1 |
| 4 | Direct laser deposition of alloys from elemental powder blends显示文摘 | Schwendner K I Banerjee R Collins P C | 2001 | Scripta Materialia2001，45，： | 1 |
| 5 | Direct laser deposition of alloys from elemental powder blends显示文摘 | Schwendner K I Banerjee R Collins P C | 2001 | Scripta Materialia2001，45，10： | 1 |
| 6 | Direct Laser Deposition of Alloys from Elemental Powder Blends 显示文摘 | Schwendner K I Banerjee R Collins P C | 2001 | Scripta Materialia2001，45，： | 1 |
| 7 | Direct laser deposition of alloys from elemental powder blends显示文摘 | Katrin I Schwendner Rajarshi Banerjee Peter C Collins | 2001 | Scripta Materialia2001，45，： | 1 |
| 8 | Role of LXRs in control of lipogenesis显示文摘 | Schultz JR Tu H Luk A Repa J J Medina JC Li L Schwendner S Wang S Thoolen M Mangelsdorf D J Lustig KD Shan B | | 0，，22： | 1 |
| 9 | Photodissociation of Ar2^+ in strong laser fields显示文摘 | Schwendner P Seyl F Schinke R | 1997 | Chem Phys1997，217，2： | 1 |
| 10 | Characterization of laser-deposited TiAl alloys显示文摘 | ZHANG X D BRICE C MAHAFFEY D W ZHANG H SCHWENDNER K EVANS D J FRASER H L | 2002 | Scripta Mater2002，44，： | 1 |
| 11 | Direct laser deposition of alloys from elemental powder blends显示文摘 | Katrin I Schwendner Rajarshi Banerjee | 2001 | Scripta Materialia2001，45，： | 1 |
| 12 | Direct laser deposition of alloys from elemental powder blends显示文摘 | SCHWENDNER K I BANERJEE R COLLINS P C | 2001 | Scripta Materialia2001，45，19： | 1 |
| 13 | Artificial Intelligence in Neuro-oncology:Friend or Foe of Neurosurgeons?显示文摘As one of the tumors with substantial treatment difficulties,brain tumors have a high mortality rate and high treatment costs.Furthermore,surgical rection of deep-seated tumors or tumors involving eloquent areas is still a challenge for neurosurgeons.Therefore,accurate and early tumor diagnosis,selection of treatment options,and prediction of prognosis are important to improve patients’outcomes.Recently,with the rapid development of computational technology,the frequency of its application in clinical work has increased enormously and the acquisition of medical data has become more convenient and efficient.Furthermore,with the advancement of artificial intelligence(AI)—particularly,machine and deep learning—the applications of AI in medicine and especially neuro-oncology have enhanced diagnosis,treatment,and prognosis prediction of brain tumors topreviously unachievable levels.This article presents an overview of the applications of AI in neuro-oncology for diagnosis,prognosis,surgical treatment,and education.Furthermore,the advantages,perspectives,and challenges of AI for clinical applications in neuro-oncology are discussed. | Zhenyu GONG Maximilian SCHWENDNER Tao XU | 2022 | Clinical Cancer Bulletin2022，1，1： | 0 |
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